Question 1

When would a large difference between the means of the control and treatment groups be very likely to be statistically significant?

Accepted Answer

A large sample size increases the power to detect statistically significant differences between the means of control and treatment groups, even if the effect size is small. Therefore, a large difference between the means of control and treatment groups would be very likely to be statistically significant when the sample size is large, regardless of whether the hypothesis is true or false, or whether the effect size is practically significant or not.

Question 2

How can sampling error be reduced?

Accepted Answer

Sampling error can be reduced by increasing the sample size. This is because as the sample size increases, the likelihood of obtaining a representative sample and reducing the impact of chance on the results also increases. Statistical tests, double-blind experiments, and monitoring changes in the experimental and control groups may help increase the validity of the results, but they do not directly address sampling error.

Question 3

Which type of study observes specific human populations for unusually high levels of a disease?

Accepted Answer

An ecological study observes specific populations in a certain geographic area for unusually high levels of a disease. This type of study looks at population-level data rather than individual-level data.

Question 4

What would result from an ideal experiment?

Accepted Answer

An ideal experiment would have low standard error, indicating that the mean values of the sample are consistent and close to the true value. High sampling error, small treatment effect, and large confidence interval would indicate that the experiment is not ideal and there is more variability or uncertainty in the results.

Question 5

When an experiment has a large sample size, and there is a large difference between the results in the experimental and control groups, how likely is it that the experimental results are statistically significant?

Accepted Answer

A large sample size and a large difference between the results in the experimental and control groups increase the power of the experiment and make it more likely to detect a statistically significant difference. Therefore, it is very likely that the experimental results are statistically significant.

Question 6

In statistics, what is a sample?

Accepted Answer

A sample is a small subgroup of a population to be studied. It is taken from the larger population and is used to draw conclusions about the population as a whole.

Question 7

What type of experimental result (two words) is one that is very unlikely to be due to chance differences between the experimental and control groups?

Accepted Answer

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Question 8

The incidence of cancer in people living within 100 yards of overhead power lines is recorded. This would be an example of what type of epidemiological technique?

Accepted Answer

This is an ecological study, as the data is being collected based on the population living in a certain geographic location, rather than following specific individuals over time (cohort study) or collecting data at one point in time (cross-sectional survey). It is also not a correlational experiment, as there is no manipulation of variables.

Question 9

Why are double-blind experiments used?

Accepted Answer

Double-blind experiments are used to make the results more objective by eliminating any potential biases that could be introduced by the experimenter or the study participants. Neither the participants nor the researcher know which participants are in the treatment group or the control group, which helps ensure that their beliefs and expectations about the treatment do not influence the results. This helps to increase the validity and reliability of the results.

Question 10

What is the scientific information collected from well-designed experiments that should allow researchers to either reject or support a hypothesis?

Accepted Answer

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Question 11

Which of the following is an example of a cohort study?

Accepted Answer

A cohort study involves following a group of individuals over time to assess the relationship between exposure to a particular factor and the development of a disease or condition. In option B, the group of individuals living in a small town are being followed over time to see if there is an increased incidence of lung cancer due to their exposure to coal plant emissions. This fits the definition of a cohort study. Options A, C, and D are not examples of cohort studies because they do not involve following a specific group of individuals over time. Option A and D are case-control studies, where individuals with and without the disease are compared retrospectively to determine exposure. Option C is a cross-sectional study, where individuals are assessed at a single point in time for both exposure and disease status.

Question 12

The average annual temperature among geographic regions is plotted on the x-axis of a graph and the spiciness of local food in that region is plotted on the y-axis. If the hotness of local food increases as the average annual temperature increases, then what can be concluded?

Accepted Answer

The question states that there is a correlation between the two variables (average temperature and spiciness of local food). However, it does not imply a causal relationship. Therefore, option D is the best choice. Option B may seem plausible, but it relies on a casual inference.

Question 13

What type of subject is treated as closely as possible to an experimental subject except that he or she does not get the experimental treatment?

Accepted Answer

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Question 14

Which of the following is a disadvantage of a correlational experiment?

Accepted Answer

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Question 15

What is a statistically significant result?

Accepted Answer

A statistically significant result is one that is unlikely to occur by chance, and is typically established when the p-value (probability of obtaining the result by chance) is less than .05. This means that the chances of the result being a fluke or coincidence are less than 5%. A statistically significant result provides evidence for a true effect or relationship between variables.

Question 16

What is the specialized branch of mathematics that is used to compare data?

Accepted Answer

Statistics is the specialized branch of mathematics that is used to compare data, involving the collection, analysis, interpretation, presentation, and organization of data. Epidemiology is the study of patterns and causes of health and disease conditions in defined populations, while computational mathematics deals with the development and use of mathematical algorithms and models for solving problems on computers. Cross-sectional mathematics is not a recognized term in mathematics or any related field.

Question 17

What is an intentionally ineffective treatment given to members of a control group in an experiment?

Accepted Answer

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Question 18

What would experimental results with very high statistical significance mean?

Accepted Answer

Very high statistical significance means that the probability of obtaining the results by chance is extremely low. This suggests that a true difference between the treatment and control groups likely exists. However, statistical significance alone does not confirm the correctness of the hypothesis, the absence of bias, or the presence of proper controls.

Question 19

Why might scientists often be hesitant to believe the results of a single experiment testing a particular treatment, even when the results are peer reviewed and statistically significant?

Accepted Answer

Scientists may be hesitant to believe the results of a single experiment testing a particular treatment because the results may not be true for humans if the experiment used a model organism. This is because model organisms can have different physiological and genetic characteristics than humans. Therefore, scientists often want to see the results of multiple experiments using different model organisms or even human trials to confirm the validity and generalizability of the findings.

Question 20

What does sampling error refer to?

Accepted Answer

Sampling error refers to the differences between a group of experimental subjects and the population as a whole. This can arise due to the random selection of subjects and other sources of variability.

Quiz 1: Can Science Cure the Common Cold Introduction to the Scientific Method