How to conduct an experiment - AP Statistics
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You and your classmate want to test the effect of food coloring on plant color. One of the groups in the experiment receives dye-free water. Which group is this?
You and your classmate want to test the effect of food coloring on plant color. One of the groups in the experiment receives dye-free water. Which group is this?
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The control group receives no treatment.
The experimental group receives the treatment of the independent variable.
Because the flowers getting no dye do not receive the treatment, it is the control group.
The control group receives no treatment.
The experimental group receives the treatment of the independent variable.
Because the flowers getting no dye do not receive the treatment, it is the control group.
You and your friend want to test the effect of different brands of fertilizer on sunflower height.
One group receives no fertilizer during the course of the experiment.
Which group is this?
You and your friend want to test the effect of different brands of fertilizer on sunflower height.
One group receives no fertilizer during the course of the experiment.
Which group is this?
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The control group receives no treatment.
The experimental group receives the treatment of the independent variable.
Because the sunflowers getting no fertilizer do not receive the treatment, it is the control group.
The control group receives no treatment.
The experimental group receives the treatment of the independent variable.
Because the sunflowers getting no fertilizer do not receive the treatment, it is the control group.
Of the following examples, which best describes quantitative data?
Of the following examples, which best describes quantitative data?
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Quantitative data describes a certain type of information that can be counted or expressed numerically and can be used in meaningful computations. Quantitative data is different from qualitative data, which is primarily involved in describing things in terms of categorizations or specific qualities. Looking at the answer choices, it is clear that measuring the temperature of water in degrees Fahrenheit is a numerical piece of information, and is thus quantitative.
Quantitative data describes a certain type of information that can be counted or expressed numerically and can be used in meaningful computations. Quantitative data is different from qualitative data, which is primarily involved in describing things in terms of categorizations or specific qualities. Looking at the answer choices, it is clear that measuring the temperature of water in degrees Fahrenheit is a numerical piece of information, and is thus quantitative.
When designing an experiment, what is the purpose of blocking?
When designing an experiment, what is the purpose of blocking?
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The purpose of blocking, by definition, is to separate a particular sample into groups previously known to be similar in some way that are expected to affect response to treatments. The other choices pertain to control (keeping an extraneous variable constant), randomization (using random chance to assign experimental units to treatments), and replication (increasing the number of experimental units to reduce chance variation) in an experiment.
The purpose of blocking, by definition, is to separate a particular sample into groups previously known to be similar in some way that are expected to affect response to treatments. The other choices pertain to control (keeping an extraneous variable constant), randomization (using random chance to assign experimental units to treatments), and replication (increasing the number of experimental units to reduce chance variation) in an experiment.
Which of the following is an example of qualitative data?
Which of the following is an example of qualitative data?
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The only example of qualitative data here is the gender of a high school student (i.e. male or female). This cannot be quantified, unlike the other answer choices which all have numbers, quantities, and amounts associated with them.
The only example of qualitative data here is the gender of a high school student (i.e. male or female). This cannot be quantified, unlike the other answer choices which all have numbers, quantities, and amounts associated with them.
A researcher wants to randomly assign participants to a treatment and control group. Which of the following approaches ensures that the treatment assignment is random?
A researcher wants to randomly assign participants to a treatment and control group. Which of the following approaches ensures that the treatment assignment is random?
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The only random procedure here is the coin flip. In expectation, the coin flip ensures that no background variables influence treatment assignment whereas the other examples either have nothing to do with random assignment (e.g. nationally representative sample) or completely contradict the purpose of random assignment (e.g. assigning the treatment based on who needs it the most).
The only random procedure here is the coin flip. In expectation, the coin flip ensures that no background variables influence treatment assignment whereas the other examples either have nothing to do with random assignment (e.g. nationally representative sample) or completely contradict the purpose of random assignment (e.g. assigning the treatment based on who needs it the most).
An company wants to test how much a fuel additive improves the fuel efficiency of cars and has 
cars of various makes and models available to test. Which experimental design would be most appropriate?
An company wants to test how much a fuel additive improves the fuel efficiency of cars and has
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A matched pairs design t test is the best choice because it will compare the effectiveness of the fuel additive by looking at the means differences of two sample sets where the only variable that is changed from one test to the other test is the introduction of the fuel additive. It makes no sense to compare the performance of, for example, a Ford Mustang with the additive against a Toyota Prius hybrid without the additive. It becomes crucial to compare fuel efficiency with and without the fuel additive for each car.
A matched pairs design t test is the best choice because it will compare the effectiveness of the fuel additive by looking at the means differences of two sample sets where the only variable that is changed from one test to the other test is the introduction of the fuel additive. It makes no sense to compare the performance of, for example, a Ford Mustang with the additive against a Toyota Prius hybrid without the additive. It becomes crucial to compare fuel efficiency with and without the fuel additive for each car.
For which of these experiments would a matched pairs design not be ideal?
For which of these experiments would a matched pairs design not be ideal?
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Remember that a matched pairs design tends to involve "before and after" or "with and without" or "left and right" using the same experimental units.
Therefore comparing effectiveness of two coaches and their methods would not be an experiment for the matched pairs design.
Remember that a matched pairs design tends to involve "before and after" or "with and without" or "left and right" using the same experimental units.
Therefore comparing effectiveness of two coaches and their methods would not be an experiment for the matched pairs design.
A drug company wants to test whether its medication reduces cancer risk. Assuming the company conducts an experiment in which participants are randomly assigned to treatment and control groups, what would the appropriate control group look like?
A drug company wants to test whether its medication reduces cancer risk. Assuming the company conducts an experiment in which participants are randomly assigned to treatment and control groups, what would the appropriate control group look like?
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The only thing you want to vary across groups when you're conducting an experiment is the treatment. Since taking pills is a part of taking medication (the treatment), medical experiments often employ something called a placebo-controlled study where outcomes for those who are randomly assigned to take the medication are compared to outcomes for those who are randomly assigned to take a sugar pill. The sugar pill is expected to have no effect, so it serves as a useful baseline to compare the treatment to.
The only thing you want to vary across groups when you're conducting an experiment is the treatment. Since taking pills is a part of taking medication (the treatment), medical experiments often employ something called a placebo-controlled study where outcomes for those who are randomly assigned to take the medication are compared to outcomes for those who are randomly assigned to take a sugar pill. The sugar pill is expected to have no effect, so it serves as a useful baseline to compare the treatment to.
In a public health study, researchers want to see how the addition of fresh produce stands in inner cities can affect the body weights of people who live within 1 mile of the stands.
The research group gathers data from several groups. Please identify which is the Control group.
In a public health study, researchers want to see how the addition of fresh produce stands in inner cities can affect the body weights of people who live within 1 mile of the stands.
The research group gathers data from several groups. Please identify which is the Control group.
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Areas A and B are both experimental areas, where they received the treatment (the new produce stand), so comparing body weights before and after the treatment will provide valuable data.
The area of the city which did not receive the treatment (a produce stand) will provide data of how body weight may change over time naturally, without the stand, in order to compare the effects of the stands elsewhere.
The nearby town already has produce stands and provides residents with a different food environment, so it cannot act as the control group. It has different conditions than the experimental areas A and B, so comparing it to these areas will not provide helpful data in terms of the treatment's effects.
Areas A and B are both experimental areas, where they received the treatment (the new produce stand), so comparing body weights before and after the treatment will provide valuable data.
The area of the city which did not receive the treatment (a produce stand) will provide data of how body weight may change over time naturally, without the stand, in order to compare the effects of the stands elsewhere.
The nearby town already has produce stands and provides residents with a different food environment, so it cannot act as the control group. It has different conditions than the experimental areas A and B, so comparing it to these areas will not provide helpful data in terms of the treatment's effects.
Alpha Corporation developed a new pill to treat elevated glucose levels. They want to test the efficiency of the pill to lower glucose levels by gathering a sample of people with high glucose and giving them either:
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A daily dose of their new pill ("Experimental Group")
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A daily placebo pill that looks the same but does not do anything ("Placebo Group")
How can they make this a "Blind Study"?
Alpha Corporation developed a new pill to treat elevated glucose levels. They want to test the efficiency of the pill to lower glucose levels by gathering a sample of people with high glucose and giving them either:
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A daily dose of their new pill ("Experimental Group")
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A daily placebo pill that looks the same but does not do anything ("Placebo Group")
How can they make this a "Blind Study"?
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A blind experiment is one in which the participant does not know which experimental group they are in-- which is accomplished by not letting them know if they are in the Experimental or Placebo group.
A blind experiment is one in which the participant does not know which experimental group they are in-- which is accomplished by not letting them know if they are in the Experimental or Placebo group.
A study is attempting to test various brands of cola against each other. Which of these would not be a measure that could be used to help create a double blind test?
A study is attempting to test various brands of cola against each other. Which of these would not be a measure that could be used to help create a double blind test?
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Remember that a double blind experiment means that neither the subject nor the person conducting the experiment knows the identity of the various treatments until the test is over, so as to minimize bias.
Therefore of the options,
serving the samples to the taster in their usual containers, is the one which would not help create a double blind test.
Remember that a double blind experiment means that neither the subject nor the person conducting the experiment knows the identity of the various treatments until the test is over, so as to minimize bias.
Therefore of the options,
serving the samples to the taster in their usual containers, is the one which would not help create a double blind test.
Which of the following is an example of a double blind experiment?
Which of the following is an example of a double blind experiment?
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A double blind experiment requires that both researchers and test subjects are unaware of who is receiving the treatment and who is receiving the placebo. If only one group is unaware, it is a single blind experiment. If both groups are aware, the experiment is not blinded.
A double blind experiment requires that both researchers and test subjects are unaware of who is receiving the treatment and who is receiving the placebo. If only one group is unaware, it is a single blind experiment. If both groups are aware, the experiment is not blinded.
Which of the following is an example of a single-blind experiment?
Which of the following is an example of a single-blind experiment?
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In a single-blind experiment, one group (either the researchers or the test subjects) must be blinded while the other group is aware of who is receiving a placebo and who is receiving a therapy.
The following two examples are correct:
-An experiment in which the test subjects are aware of who is receiving a placebo and who is receiving a therapy, but the researchers are unaware.
-An experiment in which the researchers are aware of who is receiving a placebo and who is receiving a therapy, but the test subjects are unaware.
In a single-blind experiment, one group (either the researchers or the test subjects) must be blinded while the other group is aware of who is receiving a placebo and who is receiving a therapy.
The following two examples are correct:
-An experiment in which the test subjects are aware of who is receiving a placebo and who is receiving a therapy, but the researchers are unaware.
-An experiment in which the researchers are aware of who is receiving a placebo and who is receiving a therapy, but the test subjects are unaware.
A drug company wants to test a new pill that should make people's nails grow twice as quickly as normal. How can they make the study a blind study?
A drug company wants to test a new pill that should make people's nails grow twice as quickly as normal. How can they make the study a blind study?
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In order for a study to be "blind," the participants can't know which group they are sorted into. For a study to be double-blind, which is even better, the researchers should also be blind to which group participants are in until the study is completed.
In order for a study to be "blind," the participants can't know which group they are sorted into. For a study to be double-blind, which is even better, the researchers should also be blind to which group participants are in until the study is completed.
Let us suppose a company wants to evaluate whether a new medical device works better than current devices. It conducts a small experiment to assess the effectiveness of the new device. To conduct the experiment, the company randomly assigns one group to the new medical device, which requires users to stay well hydrated, and the other group to the old device.
How should we control for confounding variables?
Let us suppose a company wants to evaluate whether a new medical device works better than current devices. It conducts a small experiment to assess the effectiveness of the new device. To conduct the experiment, the company randomly assigns one group to the new medical device, which requires users to stay well hydrated, and the other group to the old device.
How should we control for confounding variables?
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When comparing the effectiveness of a treatment, one should try to ensure that only the treatment varies across groups. In this case, the new device is compared to an old device. However, the new device also requires that users stay well hydrated. If we observe any positive effects from the new device, we won't know whether the new device is effective, or if merely staying well hydrated is actually what is effective. To rule out this confounding variable, we should also ask the group using the old machine condition to stay hydrated as well.
When comparing the effectiveness of a treatment, one should try to ensure that only the treatment varies across groups. In this case, the new device is compared to an old device. However, the new device also requires that users stay well hydrated. If we observe any positive effects from the new device, we won't know whether the new device is effective, or if merely staying well hydrated is actually what is effective. To rule out this confounding variable, we should also ask the group using the old machine condition to stay hydrated as well.
An experiment was done by medical researchers to determine the association between drinking caffeine and severity of lung cancer. Results showed that there was a high association between the two variables. Which of the following could be a potential confounding variable in the experiment?
An experiment was done by medical researchers to determine the association between drinking caffeine and severity of lung cancer. Results showed that there was a high association between the two variables. Which of the following could be a potential confounding variable in the experiment?
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A confounding variable is one that could potentially have an effect on both the independent and dependent variables in a study. In this case, it is possible that there is an association between smoking and caffeine as well as smoking and lung cancer.
A confounding variable is one that could potentially have an effect on both the independent and dependent variables in a study. In this case, it is possible that there is an association between smoking and caffeine as well as smoking and lung cancer.
A study finds that caffeine intake has a strong positive correlation with grades for college students. In other words, on average, the more caffeine intake a student has, the higher a grade the student gets.
Which of the following could potentially be a confounding variable in this experiment?
A study finds that caffeine intake has a strong positive correlation with grades for college students. In other words, on average, the more caffeine intake a student has, the higher a grade the student gets.
Which of the following could potentially be a confounding variable in this experiment?
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The only confounding variable in this experiment is the amount of sleep that each student gets. A confounding variable is one that has an impact on both the dependent and independent variable. It is possible that the amount of sleep a student gets is related to caffeine intake, which in turn affects the grade a student receives on a test or assignment.
The only confounding variable in this experiment is the amount of sleep that each student gets. A confounding variable is one that has an impact on both the dependent and independent variable. It is possible that the amount of sleep a student gets is related to caffeine intake, which in turn affects the grade a student receives on a test or assignment.
An experiment testing the effects of caffeine on endurance performance in athletes assigns caffeine to a randomly selected group of athletes and has them exercise. Another trial was conducted in which the same group exercised without anything given to them to take. The results did not match the expected results. What should be done to improve this experiment?
An experiment testing the effects of caffeine on endurance performance in athletes assigns caffeine to a randomly selected group of athletes and has them exercise. Another trial was conducted in which the same group exercised without anything given to them to take. The results did not match the expected results. What should be done to improve this experiment?
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The placebo effect can potentially be a confounding variable. By knowingly taking a substance, participants may feel more energenized. By administering the same substance both trials, with the only thing changed being caffeine content, this corrects for this possible confounding variable.
The placebo effect can potentially be a confounding variable. By knowingly taking a substance, participants may feel more energenized. By administering the same substance both trials, with the only thing changed being caffeine content, this corrects for this possible confounding variable.
A small local umbrella company is trying to test the effectiveness of their umbrellas by looking at how many umbrellas they sell each year.
In 2014, the company sold 2,000 umbrellas.
In 2015, they sold 1,500 umbrellas.
They assume that their umbrellas are less effective which is why sales decreased.
However, there could be many confounding factors. Which of the following is NOT a possible confounding factor?
A small local umbrella company is trying to test the effectiveness of their umbrellas by looking at how many umbrellas they sell each year.
In 2014, the company sold 2,000 umbrellas.
In 2015, they sold 1,500 umbrellas.
They assume that their umbrellas are less effective which is why sales decreased.
However, there could be many confounding factors. Which of the following is NOT a possible confounding factor?
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Any of these answers could explain why umbrella sales dropped. You cannot assume any specific cause explains a change in data like this-- further experimentation should be done rather than assuming cause and effect.
Any of these answers could explain why umbrella sales dropped. You cannot assume any specific cause explains a change in data like this-- further experimentation should be done rather than assuming cause and effect.