state your hypothesis about the thermometer temperatures

User Preferences

Content preview.

Arcu felis bibendum ut tristique et egestas quis:

• Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris
• Duis aute irure dolor in reprehenderit in voluptate
• Excepteur sint occaecat cupidatat non proident

Keyboard Shortcuts

S.3 hypothesis testing.

In reviewing hypothesis tests, we start first with the general idea. Then, we keep returning to the basic procedures of hypothesis testing, each time adding a little more detail.

The general idea of hypothesis testing involves:

• Making an initial assumption.
• Collecting evidence (data).
• Based on the available evidence (data), deciding whether to reject or not reject the initial assumption.

Every hypothesis test — regardless of the population parameter involved — requires the above three steps.

Example S.3.1

Is normal body temperature really 98.6 degrees f section  .

Consider the population of many, many adults. A researcher hypothesized that the average adult body temperature is lower than the often-advertised 98.6 degrees F. That is, the researcher wants an answer to the question: "Is the average adult body temperature 98.6 degrees? Or is it lower?" To answer his research question, the researcher starts by assuming that the average adult body temperature was 98.6 degrees F.

Then, the researcher went out and tried to find evidence that refutes his initial assumption. In doing so, he selects a random sample of 130 adults. The average body temperature of the 130 sampled adults is 98.25 degrees.

Then, the researcher uses the data he collected to make a decision about his initial assumption. It is either likely or unlikely that the researcher would collect the evidence he did given his initial assumption that the average adult body temperature is 98.6 degrees:

• If it is likely , then the researcher does not reject his initial assumption that the average adult body temperature is 98.6 degrees. There is not enough evidence to do otherwise.
• either the researcher's initial assumption is correct and he experienced a very unusual event;
• or the researcher's initial assumption is incorrect.

In statistics, we generally don't make claims that require us to believe that a very unusual event happened. That is, in the practice of statistics, if the evidence (data) we collected is unlikely in light of the initial assumption, then we reject our initial assumption.

Example S.3.2

Criminal trial analogy section  .

One place where you can consistently see the general idea of hypothesis testing in action is in criminal trials held in the United States. Our criminal justice system assumes "the defendant is innocent until proven guilty." That is, our initial assumption is that the defendant is innocent.

In the practice of statistics, we make our initial assumption when we state our two competing hypotheses -- the null hypothesis ( H 0 ) and the alternative hypothesis ( H A ). Here, our hypotheses are:

• H 0 : Defendant is not guilty (innocent)
• H A : Defendant is guilty

In statistics, we always assume the null hypothesis is true . That is, the null hypothesis is always our initial assumption.

The prosecution team then collects evidence — such as finger prints, blood spots, hair samples, carpet fibers, shoe prints, ransom notes, and handwriting samples — with the hopes of finding "sufficient evidence" to make the assumption of innocence refutable.

In statistics, the data are the evidence.

The jury then makes a decision based on the available evidence:

• If the jury finds sufficient evidence — beyond a reasonable doubt — to make the assumption of innocence refutable, the jury rejects the null hypothesis and deems the defendant guilty. We behave as if the defendant is guilty.
• If there is insufficient evidence, then the jury does not reject the null hypothesis . We behave as if the defendant is innocent.

In statistics, we always make one of two decisions. We either "reject the null hypothesis" or we "fail to reject the null hypothesis."

Errors in Hypothesis Testing Section  

Did you notice the use of the phrase "behave as if" in the previous discussion? We "behave as if" the defendant is guilty; we do not "prove" that the defendant is guilty. And, we "behave as if" the defendant is innocent; we do not "prove" that the defendant is innocent.

This is a very important distinction! We make our decision based on evidence not on 100% guaranteed proof. Again:

• If we reject the null hypothesis, we do not prove that the alternative hypothesis is true.
• If we do not reject the null hypothesis, we do not prove that the null hypothesis is true.

We merely state that there is enough evidence to behave one way or the other. This is always true in statistics! Because of this, whatever the decision, there is always a chance that we made an error .

Let's review the two types of errors that can be made in criminal trials:

Table S.3.2 shows how this corresponds to the two types of errors in hypothesis testing.

Note that, in statistics, we call the two types of errors by two different  names -- one is called a "Type I error," and the other is called  a "Type II error." Here are the formal definitions of the two types of errors:

There is always a chance of making one of these errors. But, a good scientific study will minimize the chance of doing so!

Making the Decision Section  

Recall that it is either likely or unlikely that we would observe the evidence we did given our initial assumption. If it is likely , we do not reject the null hypothesis. If it is unlikely , then we reject the null hypothesis in favor of the alternative hypothesis. Effectively, then, making the decision reduces to determining "likely" or "unlikely."

In statistics, there are two ways to determine whether the evidence is likely or unlikely given the initial assumption:

• We could take the " critical value approach " (favored in many of the older textbooks).
• Or, we could take the " P -value approach " (what is used most often in research, journal articles, and statistical software).

In the next two sections, we review the procedures behind each of these two approaches. To make our review concrete, let's imagine that μ is the average grade point average of all American students who major in mathematics. We first review the critical value approach for conducting each of the following three hypothesis tests about the population mean $\mu$:

In Practice

• We would want to conduct the first hypothesis test if we were interested in concluding that the average grade point average of the group is more than 3.
• We would want to conduct the second hypothesis test if we were interested in concluding that the average grade point average of the group is less than 3.
• And, we would want to conduct the third hypothesis test if we were only interested in concluding that the average grade point average of the group differs from 3 (without caring whether it is more or less than 3).

Upon completing the review of the critical value approach, we review the P -value approach for conducting each of the above three hypothesis tests about the population mean \(\mu\). The procedures that we review here for both approaches easily extend to hypothesis tests about any other population parameter.

• school Campus Bookshelves
• menu_book Bookshelves
• perm_media Learning Objects
• login Login
• how_to_reg Request Instructor Account
• hub Instructor Commons

Margin Size

• Download Page (PDF)
• Download Full Book (PDF)
• Periodic Table
• Physics Constants
• Scientific Calculator
• Reference & Cite
• Tools expand_more
• Readability

selected template will load here

This action is not available.

2.5: Body Temperature Homeostasis

• Last updated
• Save as PDF
• Page ID 41655

• Karri Haen Whitmer
• Iowa State University via Iowa State University Digital Press

\( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

\( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

\( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\)

( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\)

\( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

\( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\)

\( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

\( \newcommand{\Span}{\mathrm{span}}\)

\( \newcommand{\id}{\mathrm{id}}\)

\( \newcommand{\kernel}{\mathrm{null}\,}\)

\( \newcommand{\range}{\mathrm{range}\,}\)

\( \newcommand{\RealPart}{\mathrm{Re}}\)

\( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

\( \newcommand{\Argument}{\mathrm{Arg}}\)

\( \newcommand{\norm}[1]{\| #1 \|}\)

\( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\AA}{\unicode[.8,0]{x212B}}\)

\( \newcommand{\vectorA}[1]{\vec{#1}}      % arrow\)

\( \newcommand{\vectorAt}[1]{\vec{\text{#1}}}      % arrow\)

\( \newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

\( \newcommand{\vectorC}[1]{\textbf{#1}} \)

\( \newcommand{\vectorD}[1]{\overrightarrow{#1}} \)

\( \newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}} \)

\( \newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}} \)

Maintaining homeostasis requires that the body continuously monitors its internal conditions. From body temperature to blood pressure to levels of certain nutrients, each physiological condition has a particular set point. A set point is the physiological value around which the normal range fluctuates. A normal range is the restricted set of values that is optimally healthful and stable. For example, the set point for normal human body temperature is approximately 37°C (98.6°F). Physiological parameters, such as body temperature and blood pressure, tend to fluctuate within a normal range a few degrees above and below that point. Control centers in the brain and other parts of the body monitor and react to deviations from homeostasis using negative feedback. Negative feedback is a mechanism that reverses a deviation from the set point. Therefore, negative feedback maintains body parameters within their normal range. The maintenance of homeostasis by negative feedback goes on throughout the body at all times.

The human body regulates body temperature through a process called thermoregulation, in which the body can maintain its temperature within certain boundaries, even when the surrounding temperature is very different. The core temperature of the body remains steady at around 36.5–37.5 °C (or 97.7–99.5 °F). In the process of ATP production by cells throughout the body, approximately 60 percent of the energy produced is in the form of heat used to maintain body temperature. Thermoregulation is an example of negative feedback.

The hypothalamus in the brain is the master switch that works as a thermostat to regulate the body’s core temperature (Figure 1). If the temperature is too high, the hypothalamus can initiate several processes to lower it. These include increasing the circulation of the blood to the surface of the body to allow for the dissipation of heat through the skin and initiation of sweating to allow evaporation of water on the skin to cool its surface. Conversely, if the temperature falls below the set core temperature, the hypothalamus can initiate shivering to generate heat. The body uses more energy and generates more heat. In addition, thyroid hormone will stimulate more energy use and heat production by cells throughout the body. An environment is said to be thermoneutral when the body does not expend or release energy to maintain its core temperature. For a naked human, this is an ambient air temperature of around 84 °F. If the temperature is higher, for example, when wearing clothes, the body compensates with cooling mechanisms. The body loses heat through the mechanisms of heat exchange.

Mechanisms of Heat Exchange

When the environment is not thermoneutral, the body uses four mechanisms of heat exchange to maintain homeostasis: conduction, convection, radiation, and evaporation. Each of these mechanisms relies on the property of heat to flow from a higher concentration to a lower concentration; therefore, each of the mechanisms of heat exchange varies in rate according to the temperature and conditions of the environment.

Conduction is the transfer of heat by two objects that are in direct contact with one another. It occurs when the skin comes in contact with a cold or warm object. For example, when holding a glass of ice water, the heat from your skin will warm the glass and in turn melt the ice. Alternatively, on a cold day, you might warm up by wrapping your cold hands around a hot mug of coffee. Only about 3 percent of the body’s heat is lost through conduction.

Convection is the transfer of heat to the air surrounding the skin. The warmed air rises away from the body and is replaced by cooler air that is subsequently heated. Convection can also occur in water. When the water temperature is lower than the body’s temperature, the body loses heat by warming the water closest to the skin, which moves away to be replaced by cooler water. The convection currents created by the temperature changes continue to draw heat away from the body more quickly than the body can replace it, resulting in hypothermia. About 15 percent of the body’s heat is lost through convection.

Radiation is the transfer of heat via infrared waves. This occurs between any two objects when their temperatures differ. A radiator can warm a room via radiant heat. On a sunny day, the radiation from the sun warms the skin. The same principle works from the body to the environment. About 60 percent of the heat lost by the body is lost through radiation.

Evaporation is the transfer of heat by the evaporation of water. Because it takes a great deal of energy for a water molecule to change from a liquid to a gas, evaporating water (in the form of sweat) takes with it a great deal of energy from the skin. However, the rate at which evaporation occurs depends on relative humidity—more sweat evaporates in lower humidity environments. Sweating is the primary means of cooling the body during exercise, whereas at rest, about 20 percent of the heat lost by the body occurs through evaporation.

Homeostatic Response to Environmental Temperatures

Humans have a temperature regulation feedback system that works by promoting either heat loss or heat gain. When the brain’s temperature regulation center receives data from the sensors indicating that the body’s temperature exceeds its normal range, it stimulates a cluster of brain cells referred to as the “heat-loss center.” This stimulation has three major effects:

• Blood vessels in the skin begin to dilate allowing more blood from the body core to flow to the surface of the skin allowing the heat to radiate into the environment.
• As blood flow to the skin increases, sweat glands are activated to increase their output. As the sweat evaporates from the skin surface into the surrounding air, it takes heat with it.
• The depth of respiration increases, and a person may breathe through an open mouth instead of through the nasal passageways. This increases heat loss from the lungs.

In contrast, activation of the brain’s heat-gain center by exposure to cold reduces blood flow to the skin, and blood returning from the limbs is diverted into a network of deep veins (Figure 2). This arrangement traps heat closer to the body core, restricts heat loss, and increases blood pressure. If heat loss is severe, the brain triggers an increase in random signals to skeletal muscles, causing them to contract and producing shivering. The muscle contractions of shivering release heat while using ATP. The brain also triggers the thyroid gland in the endocrine system to release thyroid hormone, which increases metabolic activity and heat production in cells throughout the body.

During acute exposure to cold conditions in the body:

• Activation of the sympathetic nervous system results in system-wide discharge of catecholamine (norepinephrine).
• Catecholamine causes systemic arteriolar constriction, increased heart rate and heart contractility. The heart works harder to push blood through the narrowed blood vessels.
• Constricted blood vessels in the extremities divert superficial blood flow to the body’s core, thus, reducing the radiation or conduction of heat into the environment.
• Vasoconstriction increases the resistance to blood flow, and thus, increases blood pressure.
• Vasoconstriction leads to a weaker pulse (lower pulse amplitude) in the arteries of the skin, fingers and hand.

The Cold Pressor Test

Acute cold stress results in activation of the sympathetic nervous system and release of catecholamines (neurotransmitters). The release of neurotransmitter effects the cardiovascular system in a number of ways, including arterial constriction, transient tachycardia, and increased contractility of the heart. Together, these homeostatic changes result in what is called a pressor response , or an increase in blood pressure. The cold pressor test is commonly used in the clinical setting to evaluate the function of the sympathetic nervous system. In the cold pressor test, subjects immerse their hand or forearm in ice water, and their cardiovascular response is measured.

In this laboratory, we will use the cold pressor test to evaluate changes in heart rate, pulse amplitude, and arterial oxygen saturation using a pulse oximeter.

Pulse oximeters indirectly estimate the arterial oxygen saturation and report it as the oxygen saturation (SpO2) of the subject’s arterial blood. SpO2 is reported as a percentage of oxygenated hemoglobin. Normal pulse oximetry values typically range from 97-100%.

Cold pressor response experiment:

There are several hypotheses that could be testing In this laboratory. For example, we may test whether males and females have a different cold pressor response, or we may test whether the pressor response is the same in the submerged versus the non-submerged hand. After collecting the data, you will enter it into an excel file at the TA’s bench for a class-wide or course-wide statistical analysis.

In preparation for lab, can you write an IF/THEN hypothesis for testing the cold pressor response in men and women?

Laboratory Methods

In this lab you will conduct an experiment to test how acute cold exposure affects pulse amplitude, heart rate and hemoglobin-oxygen binding in men and women. You will be using a finger sensor called a pulse oximeter, which will measure the pulse as well as the peripheral arterial blood oxygenation (SpO2) in your finger.

Equipment Required

iWire-PO2-100

Pulse oximeter

Heating pad

Lab activity highlights

• We will use iWorx with LabScribe to interpret pulse amplitude, heart rate and SpO2.
• Subjects should not wear nail polish, artificial nail coverings, hand or wrist jewelry during the experiment.
• Subjects must wear short sleeves or sleeves that can be rolled up above the elbow.
• All subjects will participate in either “Baseline/Condition 1” or “Baseline/Condition 2” but not both.
• All subjects will submerge their LEFT forearm in the experiments.
• Because the pulse oximeter works by detecting pulsation of blood vessels, subjects should sit quietly and motionless during the experiment. Other movements or vibrations could confound the pulse oximeter readings.

Getting Started

• Turn on the iWorx unit at the switch on the back of the box
• Log into your account and click the Folder icon in the lower left task bar
• Click “ This PC ” in the left side task bar
• Double click Biol 256L Course Materials P-Drive under “ Network Locations ”
• Double click the “ Week4_ColdPressor ” settings file
• Place the pulse oximeter on the middle finger of the left (condition 1) or right (condition 2) hand as shown in the figure below.
• You are now ready to start the experiment.

EXPERIMENT: Effects of Cold Pressor Test on Cardiovascular Functioning

IMPORTANT: This experiment requires half of the subjects to participate in Baseline/Condition 1 and half of the subjects to participate in Baseline/Condition 2. At your lab table, assign each student a condition before starting the experiment.

• CONTROL/CONDITION 1: Outfit the middle finger of the left hand with the pulse oximeter. Be prepared to submerge the left forearm in ice water at the one-minute mark.
• CONTROL/CONDITION 2: Outfit the middle finger of the right hand with the pulse oximeter. Be prepared to submerge the left forearm in ice water at the one-minute mark.

PART I. Procedure

• Check the sensor: click on the red Record
• Click on the AutoScale button at the upper task bar. Your recording should look like the traces seen below in Figure 5. If the data does not appear as shown, slightly adjust the oximeter on the finger.
• Note the location of the Time in the upper right corner of the window (Fig. 5b). In the figure, the time reads “one minute and twenty-two seconds.” You will keep track of the time of the data recording with this timer on the Labscribe window.

• When the signals being recorded are suitably displayed, stop the recording and open a new file.
• As the subject sits quietly (without moving) record baseline data for one minute .
• At exactly the one-minute mark , submerge the left forearm in the ice water. DO NOT put the hand with instrumentation in the water. Remain as still as possible!
• Record the data for at least an additional 35 seconds (you may record more).
• Stop recording.
• You may dry your arm off and warm it on a heating pad. You are done serving as subject after a single exposure to the ice bath.
• Save the data file to the computer. Put the subject’s name and Week 4 in the title.

PART II. Data Analysis

This data analysis applies to both the baseline recording and to Condition 1 or 2. For baseline data, start at the very beginning of the recording and find the correct data by scrolling and using the timer on the main window.

For the experimental data (condition 1 or 2), start data analysis at the 1.00 mark and scroll to 1.05 (five seconds), 1.10 (ten seconds), 1.20 (twenty seconds) and 1.30 (thirty seconds).

To begin the data analysis:

• Use the Display Time icon to adjust the Display Time of the Main window to show approximately ten complete Pulse cycles on the Main window.
• Scroll through the recording to view exemplary pulse waves at these intervals during data recording: 5 seconds, 10 seconds, 20 seconds and 30 seconds
• Start at a pulse wave at around 5 seconds of data recording and click the double cursor icon and place the cursors as follows:
• To measure the pulse wave amplitude , place one cursor on the baseline that precedes the pulse wave and the second cursor on the peak of the pulse wave. The value for V2-V1 on the Pulse channel is this amplitude. Determine the pulse amplitude V2-V1 for the four pulse waves at the designated times and record the results in your lab report .

• To find the heart rate , select the one cursor icon and place the single cursor at the plateau of the of a heart rate trace on the Heart Rate channel . See the orange cursor in the picture below. Record the value in BPM on your lab report for heart rate data collected at approximately 5s, 10s, 20s and 30s.

• To find the SpO2 , place cursor on the data at the 30 second mark of recording. Usually this line is completely flat.
• Record the SpO2 percent , shown on the O2 Saturation channel, in your lab report.

After recording the data in your lab report, open a new file for the next student.

Students may be asked to submit these data for statistical analysis:

Note: please submit your sex (M or F) and age with your data.

• Baseline avg. heart rate
• Baseline avg. pulse wave amplitude
• Condition 1 avg. cold pressor heart rate
• Condition 1 avg. cold pressor pulse wave amplitude
• Condition 2 avg. cold pressor heart rate
• Condition 2 avg. cold pressor pulse wave amplitude
• Some background materials adapted from OpenStax Anatomy and Physiology, https://openstax.org/details/books/anatomy-and-physiology . Available for free under a CC-by-4.0 license .
• OpenStax College (2013, April 25). Anatomy and physiology . OpenStax College. Retrieved from http://cnx.org/content/col11496/latest

Cool Science Experiments Headquarters

Making Science Fun, Easy to Teach and Exciting to Learn!

Science Experiments

Easy Water Temperature Science Experiment + Video & Lab Kit

Can you see thermal energy? Yes, with just a few common kitchen items!

Although we can explain that molecules move faster when hot and slower when cold, in this science experiment kids will be able to see thermal energy in action and explore the concept hands-on.

We’ve included a materials list, printable instructions, and a simple explanation of how the experiment works. Enjoy our demonstration video to get started!

JUMP TO SECTION: Instructions | Video Tutorial | How it Works

Supplies Needed

• 3 Glass Jars
• Room Temperature Water
• Food Coloring

Water Temperature Science Lab Kit – Only $5

Use our easy Water Temperature Science Lab Kit to grab your students’ attention without the stress of planning!

It’s everything you need to  make science easy for teachers and fun for students  — using inexpensive materials you probably already have in your storage closet!

Water Temperature Science Experiment Instructions

Step 1 – Begin by preparing three identical jars of water. Fill one jar with cold water, one jar with room temperature water, and one jar with hot water.

Helpful Tip: For cold water, fill the jar and put it in the fridge for an hour or two. For the room temperature water, fill the jar and leave it on the counter for an hour or two. For the hot water, boil the water on the stove or put it in the microwave for a minute or two.

Before moving to the next step, take a moment to observe the jars. The temperature of water should be the only difference. Do you think the water temperature will impact what happens when the food coloring is added to each jar? Write down your hypothesis (prediction) and then continue the experiment to see if you were correct.

Step 2 – Place 2-3 drops of food coloring in each jar and observe what happens.

You’ll notice right away that the food coloring behaves differently in each jar. Was your hypothesis correct? Do you know why the food coloring slowly mixed with the cold water and quickly mixed with the hot water? Read the how does this experiment work section before to find out the answer. 

Video Tutorial

How Does The Experiment Work?

When observing the food coloring in the water, you will immediately notice that it behaves differently based on the temperature of the water.

Even though the glasses of water look the same, the difference in the water temperature causes the molecules that make up the water to behave differently. Molecules that make up matter move faster when they are warmer because they have more thermal energy and slower when they are colder because they have less thermal energy. In this experiment, the molecules in the hot water are moving around much faster than the molecules in the cold water.

Thermal Energy is the total energy of the particles in an object.

When placed into water, food coloring will begin to mix with the water. The food coloring will mix the fastest in the hot water because the molecules are moving fast due to their increased thermal energy. These fast-moving molecules are pushing the molecules of food coloring around as they move, causing the food coloring to spread faster.

The food coloring in the room temperature water will take longer to mix with the water because the molecules are moving more slowly due to their decreased thermal energy.

Lastly, the food coloring in the cold water will take a long time to mix with the water because the molecules are moving even slower due to a further decrease in thermal energy.

More Science Fun

Eventually, the food coloring will mix throughout all of the jars. Expand on the experiment, by estimating how long it will take to mix with the water in each jar. Then set a timer and find out how close your estimate was.

In addition, you can also try these other fun experiments using water and food coloring:

• Walking Water Science Experiment – Can water walk upwards against gravity? No, not really, but what makes water seem like it defies gravity is what we’re going to explore in this easy science experiment.
• Color Changing Walking Water Science Experiment   – Much like the regular walking water science experiment, but with an added “colorful” twist.
• Coloring Changing Water Science Experiment – Science or magic? Try this experiment at home with your kids and watch their eyes light up as you pour the liquid into the bowl and “create” a new color.

Water Temperature Experiment

• Three Glass Jars

Instructions

• Begin by preparing three jars of water. Fill one with cold water, one with room temperature water, and one with hot water. Helpful Tip: For cold water, fill the jar and put it in the fridge for an hour or two. For the room temperature water, fill the jar and leave it on the counter for an hour or two. For the hot water, boil the water on the stove or put it in the microwave for a minute or two.
• Place 2-3 drops of food coloring in each jar.
• Observe what happens to the food coloring. Does it behave differently in each jar?

Reader Interactions

May 5, 2017 at 1:17 pm

thank you for u showing my kids this they love it.

March 30, 2019 at 11:58 pm

You’re amazing!!!!

April 7, 2022 at 10:35 am

I like it a lot it’s so cool that I did it for my class and got a A+

March 9, 2022 at 6:10 pm

I will be using this at Parent Science Night tomorrow!

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

• Privacy Policy
• Disclosure Policy

Copyright © 2024 · Cool Science Experiments HQ

• school Campus Bookshelves
• menu_book Bookshelves
• perm_media Learning Objects
• login Login
• how_to_reg Request Instructor Account
• hub Instructor Commons

Margin Size

• Download Page (PDF)
• Download Full Book (PDF)
• Periodic Table
• Physics Constants
• Scientific Calculator
• Reference & Cite
• Tools expand_more
• Readability

selected template will load here

This action is not available.

7.9: Office Temperature

• Last updated
• Save as PDF
• Page ID 7121

• Foster et al.
• University of Missouri-St. Louis, Rice University, & University of Houston, Downtown Campus via University of Missouri’s Affordable and Open Access Educational Resources Initiative

\( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

\( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

\( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\)

( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\)

\( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

\( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\)

\( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

\( \newcommand{\Span}{\mathrm{span}}\)

\( \newcommand{\id}{\mathrm{id}}\)

\( \newcommand{\kernel}{\mathrm{null}\,}\)

\( \newcommand{\range}{\mathrm{range}\,}\)

\( \newcommand{\RealPart}{\mathrm{Re}}\)

\( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

\( \newcommand{\Argument}{\mathrm{Arg}}\)

\( \newcommand{\norm}[1]{\| #1 \|}\)

\( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\AA}{\unicode[.8,0]{x212B}}\)

\( \newcommand{\vectorA}[1]{\vec{#1}}      % arrow\)

\( \newcommand{\vectorAt}[1]{\vec{\text{#1}}}      % arrow\)

\( \newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

\( \newcommand{\vectorC}[1]{\textbf{#1}} \)

\( \newcommand{\vectorD}[1]{\overrightarrow{#1}} \)

\( \newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}} \)

\( \newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}} \)

Let’s do another example to solidify our understanding. Let’s say that the office building you work in is supposed to be kept at 74 degree Fahrenheit but is allowed to vary by 1 degree in either direction. You suspect that, as a cost saving measure, the temperature was secretly set higher. You set up a formal way to test your hypothesis.

Step 1: State the Hypotheses You start by laying out the null hypothesis:

\(H_0\): There is no difference in the average building temperature

\(H_0: \mu = 74\)

Next you state the alternative hypothesis. You have reason to suspect a specific direction of change, so you make a one-tailed test:

\(H_A\): The average building temperature is higher than claimed

\(\mathrm{H}_{\mathrm{A}}: \mu>74\)

Step 2: Find the Critical Values You know that the most common level of significance is \(α\) = 0.05, so you keep that the same and know that the critical value for a one-tailed \(z\)-test is \(z*\) = 1.645. To keep track of the directionality of the test and rejection region, you draw out your distribution:

Step 3: Calculate the Test Statistic Now that you have everything set up, you spend one week collecting temperature data:

You calculate the average of these scores to be \(\overline{\mathrm{X}}\)= 76.6 degrees. You use this to calculate the test statistic, using \(μ\) = 74 (the supposed average temperature), \(σ\) = 1.00 (how much the temperature should vary), and \(n\) = 5 (how many data points you collected):

\[z=\dfrac{76.60-74.00}{1.00 / \sqrt{5}}=\dfrac{2.60}{0.45}=5.78 \nonumber \]

This value falls so far into the tail that it cannot even be plotted on the distribution!

Step 4: Make the Decision You compare your obtained \(z\)-statistic, \(z\) = 5.77, to the critical value, \(z*\) = 1.645, and find that \(z > z*\). Therefore you reject the null hypothesis, concluding:

Based on 5 observations, the average temperature (\(\overline{\mathrm{X}}\)= 76.6 degrees) is statistically significantly higher than it is supposed to be, \(z\) = 5.77, \(p\) < .05.

Because the result is significant, you also calculate an effect size:

\[d=\dfrac{76.60-74.00}{1.00}=\dfrac{2.60}{1.00}=2.60 \nonumber \]

The effect size you calculate is definitely large, meaning someone has some explaining to do!

• school Campus Bookshelves
• menu_book Bookshelves
• perm_media Learning Objects
• login Login
• how_to_reg Request Instructor Account
• hub Instructor Commons

Margin Size

• Download Page (PDF)
• Download Full Book (PDF)
• Periodic Table
• Physics Constants
• Scientific Calculator
• Reference & Cite
• Tools expand_more
• Readability

selected template will load here

This action is not available.

16.4: How Temperature Influences Solubility

• Last updated
• Save as PDF
• Page ID 53852

\( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

\( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

\( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\)

( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\)

\( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

\( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\)

\( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

\( \newcommand{\Span}{\mathrm{span}}\)

\( \newcommand{\id}{\mathrm{id}}\)

\( \newcommand{\kernel}{\mathrm{null}\,}\)

\( \newcommand{\range}{\mathrm{range}\,}\)

\( \newcommand{\RealPart}{\mathrm{Re}}\)

\( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

\( \newcommand{\Argument}{\mathrm{Arg}}\)

\( \newcommand{\norm}[1]{\| #1 \|}\)

\( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\AA}{\unicode[.8,0]{x212B}}\)

\( \newcommand{\vectorA}[1]{\vec{#1}}      % arrow\)

\( \newcommand{\vectorAt}[1]{\vec{\text{#1}}}      % arrow\)

\( \newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

\( \newcommand{\vectorC}[1]{\textbf{#1}} \)

\( \newcommand{\vectorD}[1]{\overrightarrow{#1}} \)

\( \newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}} \)

\( \newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}} \)

Nuclear power plants require large amounts of water to generate steam for turbines and to cool equipment. They are usually situated near bodies of water to use that water as a coolant, returning the warmer water back to the lake or river. This increases the overall temperature of the water, which lowers the quantity of dissolved oxygen, affecting the survival of fish and other organisms.

How Temperature Influences Solubility

The solubility of a substance is the amount of that substance that is required to form a saturated solution in a given amount of solvent at a specified temperature. Solubility is often measured as the grams of solute per \(100 \: \text{g}\) of solvent. The solubility of sodium chloride in water is \(36.0 \: \text{g}\) per \(100 \: \text{g}\) water at \(20^\text{o} \text{C}\). The temperature must be specified because solubility varies with temperature. For gases, the pressure must also be specified. Solubility is specific for a particular solvent. In this section, we will consider solubility of material in water as solvent.

The solubility of the majority of solid substances increases as the temperature increases. However, the effect is difficult to predict and varies widely from one solute to another. The temperature dependence of solubility can be visualized with the help of a solubility curve , a graph of the solubility vs. temperature (see figure below).

Notice how the temperature dependence of \(\ce{NaCl}\) is fairly flat, meaning that an increase in temperature has relatively little effect on the solubility of \(\ce{NaCl}\). The curve for \(\ce{KNO_3}\), on the other hand, is very steep, and so an increase in temperature dramatically increases the solubility of \(\ce{KNO_3}\).

Several substances—\(\ce{HCl}\), \(\ce{NH_3}\), and \(\ce{SO_2}\)—have solubility that decreases as temperature increases. They are all gases at standard pressure. When a solvent with a gas dissolved in it is heated, the kinetic energy of both the solvent and solute increase. As the kinetic energy of the gaseous solute increases, its molecules have a greater tendency to escape the attraction of the solvent molecules and return to the gas phase. Therefore, the solubility of a gas decreases as the temperature increases.

Solubility curves can be used to determine if a given solution is saturated or unsaturated. Suppose that \(80 \: \text{g}\) of \(\ce{KNO_3}\) is added to \(100 \: \text{g}\) of water at \(30^\text{o} \text{C}\). According to the solubility curve, approximately \(48 \: \text{g}\) of \(\ce{KNO_3}\) will dissolve at \(30^\text{o} \text{C}\). This means that the solution will be saturated since \(48 \: \text{g}\) is less than \(80 \: \text{g}\). We can also determine that there will be \(80 - 48 = 32 \: \text{g}\) of undissolved \(\ce{KNO_3}\) remaining at the bottom of the container. In a second scenario, suppose that this saturated solution is heated to \(60^\text{o} \text{C}\). According to the curve, the solubility of \(\ce{KNO_3}\) at \(60^\text{o} \text{C}\) is about \(107 \: \text{g}\). The solution, in this case, is unsaturated since it contains only the original \(80 \: \text{g}\) of dissolved solute. Suppose in a third case, that the solution is cooled all the way down to \(0^\text{o} \text{C}\). The solubility at \(0^\text{o} \text{C}\) is about \(14 \: \text{g}\), meaning that \(80 - 14 = 66 \: \text{g}\) of the \(\ce{KNO_3}\) will recrystallize.

• The solubility of a substance is the amount of that substance that is required to form a saturated solution in a given amount of solvent at a specified temperature.
• A solubility curve is a graph of the solubility vs. temperature
• The solubility of a solid in water increases with an increase in temperature.
• Gas solubility decreases as the temperature increases.

Premium Content

• MIND, BODY, WONDER

Extreme heat can be deadly – here’s how to know if you’re at risk

A new forecast tool from the CDC and the National Weather Service helps you figure out when the heat can harm your health.

This past week, extremely high temperatures blanketed much of the South and Western United States. But figuring out whether conditions are too hot for people to safely conduct their normal outdoor activities is trickier than it might seem.

That’s why the U.S. Centers for Disease Control and Prevention and the National Oceanic and Atmospheric Administration’s National Weather Service launched a new website in April to forecast when people are especially at risk.

Thermometer readings and accompanying humidity levels aren’t the only factors determining safety when it comes to heat, says Aaron Bernstein, director of the National Center for Environmental Health at the CDC. Other important elements include elevated nighttime temperatures, which prevent the body from cooling down; whether hot days are outside of traditionally warm seasons; the duration of the heat (many days versus just one or two); and whether temperatures breach the top 5 percent of the record-high days for a given location.

“A hundred degrees in Boston is not the same as 100 degrees in Houston, when it comes to how heat affects health,” Bernstein says. The disparity flows in part because New England residents are not as accustomed to avoiding the outdoors during the hottest part of the day and because fewer likely have air conditioning in their homes, among other factors. The new forecast tool, called HeatRisk , takes all this into consideration when grading health impacts from heat across the U.S. The tool uses a five-color code ranging from green (no risk) to magenta (extreme risk).

Another important feature is it forecasts seven days. Currently, heat advisories from the National Weather Service are issued just 12 hours before dangerous temperature conditions emerge.

“If you have an event planned six days from now for the middle of the afternoon on a day when the heat risk level is red, if you can move it to a time of day that is cooler or to another day, you have the opportunity to do that,” Bernstein says.

For Hungry Minds

Heat kills thousands of americans each year.

Although other phenomena like floods, tornados, hurricanes, and even cold are often more dramatic, heat waves are the most deadly weather events in the U.S., killing more than twice as many people as any other. In 2023, 2,300 Americans died from heat-related illnesses , according to preliminary data. It’s a number that has been rising for several years.

Moreover, the official fatality figure is a severe undercount, says Jane Gilbert, the chief heat officer for Florida’s Miami-Dade County. Deaths on hot days due to heart attacks or kidney disease, which are exacerbated by temperature, or accidents occurring after someone gets woozy from heat, aren’t generally included.

Experts have linked extreme heat to increased hospital visits by people with diabetes , kidney disease , and mental-health issues including anxiety and mood disorders, as well as to pregnancy complications .

Heat also boosts the risk of dehydration and muscle cramps, as well as the nausea, fatigue, and dizziness caused by heat exhaustion. At this point, if respite from the heat is not quickly achieved, heatstroke can follow. This dangerous condition, where the body’s internal temperature rises to 104-degrees Fahrenheit, results in confusion, vomiting, loss of consciousness, and potentially permanent brain or organ damage, as well as death.

( Here’s what extreme heat does to the body .)

More hot days. Longer heat waves.

With climate change causing more frequent and longer heat waves worldwide, recognizing when heat can be deadly is essential, says Kurt Shickman, formerly the director of the extreme heat initiative at the nonprofit Adrienne Arsht-Rockefeller Foundation Resilience Center in Washington, D.C.

Experts say climate change exacerbated the African heat wave in April that killed 102 people during a four-day period, as well as last July’s blazing temperatures in Phoenix, where thermometers soared above 100 degrees every day of the month .

You May Also Like

What happens to your body when you’re in love—and when you’re heartbroken

Do you really need 10,000 steps a day? Here’s what the science says.

Here’s what extreme heat does to the body

Climate change is also responsible for more hot days outside of waves, which carries its own perils. One analysis found numerous excess deaths occur during regular hot days in the U.S. when temperatures reach the 80s or 90s.

( How heat can make you sick—and kill you )

Colored alerts separate risk levels

The HeatRisk color-coding system identifies who is most at risk for heat related health issues under specific conditions.

A yellow alert indicates that most people in a particular location can safely be outdoors all day. But the same isn’t true for sensitive people who develop headaches or heat-triggered symptoms when temperatures rise.

Orange alerts indicate danger for older people and children , pregnant women, those with chronic medical conditions including heart disease or poor circulation, and people taking medications that interfere with internal heat regulation. This includes diuretics and certain antipsychotics, antidepressants, and antihypertensives.

When the alert blinks red or magenta, everyone in that geographic area is potentially in peril. More than one in five heat-related deaths in the U.S. have occurred in people considered in the prime health years, ages 15 to 44.

Outdoor workers are an especially vulnerable population, Shickman says. “There is a need for a more concerted approach to outdoor workplace safety,” with employer-provided shade, rest, and water breaks becoming standard business practice, he says.

When heat is deadly

When a given area is under an orange heat alert, the CDC advises people at risk to stay hydrated, avoid the sun during the hottest parts of the day, and use air conditioners or open windows and turn fans on at night to cool down.

On red-alert days, which the National Weather Service notes are common in the southern U.S., everyone is advised to stay hydrated, remain indoors, ideally shift outdoor plans to another day or reschedule to a cooler time, and to find a location with air conditioning for at least a few hours.

On magenta days, people should “strongly consider” cancelling outdoor activities and check on neighbors who may need extra assistance.

Air quality levels additionally influence health on hot days, Bernstein notes. This is partly because people without air conditioning tend to open windows more and increase their exposure to toxins in the air, including smoke from area wildfires. Higher temperatures also often coincide with stagnant air that traps smog or ozone pollutants.

( Ground-level ozone is getting worse. Here’s what it means .)

Because of this link between heat and air quality, the CDC recently released a HeatRisk dashboard that allows people to enter their zip code and view both metrics for their geographic area.

Bernstein hopes the online tools protect the growing number of Americans at risk from heat. “Our goal is to make sure we have new pathways to continually keep people safe,” he says.

“We see a real need to bring attention in places where heat has not been a challenge historically,” he says, as well as to areas traditionally prone that may not realize hot days are more persistent now.

Related Topics

• PUBLIC HEALTH
• MENTAL HEALTH

Multiple COVID infections can lead to chronic health issues. Here’s what to know.

Your body needs whole grains. Here’s how to find the most effective ones.

Salmonella can be deadly. Here’s how to protect yourself from it.

E-bikes are good for the environment—but what about your health?

How ultra-processed food harms the body and brain

• Environment
• Perpetual Planet

History & Culture

• History & Culture
• History Magazine
• Mind, Body, Wonder
• Paid Content
• Terms of Use
• Privacy Policy
• Your US State Privacy Rights
• Children's Online Privacy Policy
• Interest-Based Ads
• About Nielsen Measurement
• Do Not Sell or Share My Personal Information
• Nat Geo Home
• Attend a Live Event
• Book a Trip
• Inspire Your Kids
• Shop Nat Geo
• Visit the D.C. Museum
• Learn About Our Impact
• Support Our Mission
• Advertise With Us
• Customer Service
• Renew Subscription
• Manage Your Subscription
• Work at Nat Geo
• Sign Up for Our Newsletters
• Contribute to Protect the Planet

Copyright © 1996-2015 National Geographic Society Copyright © 2015-2024 National Geographic Partners, LLC. All rights reserved