Question 1

In a hypothesis test, a significance level of 0.05 was chosen. How would you interpret this value?

Accepted Answer

In a hypothesis test, the significance l

Question 2

The sample mean of a variable is found to be 35.7. The true population mean of that variable was known to be 40.2. What is the sampling error of the variable?

Accepted Answer

A)  4.20 
B)  9.00 
C)  4.50 
D)  2.25 
A)  4.20 
B)  9.00 
C)  4.50 
D)  2.25

Question 3

Why does sampling from a population introduce uncertainty into the sample estimates?

Accepted Answer

A)  variation in samples drawn from the population 
B)  systematic error in samples drawn 
C)  changes in population due to time 
D)  estimates different from population statistics 
A)  variation in samples drawn from the population 
B)  systematic error in samples drawn 
C)  changes in population due to time 
D)  estimates different from population statistics

Question 4

The sample mean of a variable is 137.6, and is reported with an associated p value of 0.001. How could this p value be interpreted as?

Accepted Answer

A)  Probability of .999 that true mean is null, when sample mean is 137.6. 
B)  The chance of the population or true mean being 137.6 is 0.001. 
C)  Probability of .001 that population mean is 0, when sample mean is 137.6. 
D)  99.9% chance that the true mean is greater than 137.6. 
A)  Probability of .999 that true mean is null, when sample mean is 137.6. 
B)  The chance of the population or true mean being 137.6 is 0.001. 
C)  Probability of .001 that population mean is 0, when sample mean is 137.6. 
D)  99.9% chance that the true mean is greater than 137.6.

Question 5

Inferential statistics means reaching a conclusion about characteristics of a population based on sample data.

Accepted Answer

A) True 
 B)False

Question 6

A "point estimate" is a summary statistic, such as the mean or proportion, of the population.

Accepted Answer

A) True 
 B)False

Question 7

Describe the steps in developing a hypothesis test. Walk through these steps with an example.

Accepted Answer

Developing a hypothesis test involves se

In a hypothesis test, a significance level of 0.05 was chosen. How would you interpret this value?

The sample mean of a variable is found to be 35.7. The true population mean of that variable was known to be 40.2. What is the sampling error of the variable?

Why does sampling from a population introduce uncertainty into the sample estimates?

The sample mean of a variable is 137.6, and is reported with an associated p value of 0.001. How could this p value be interpreted as?

Inferential statistics means reaching a conclusion about characteristics of a population based on sample data.

A "point estimate" is a summary statistic, such as the mean or proportion, of the population.

Describe the steps in developing a hypothesis test. Walk through these steps with an example.

Introduction to Making Sense of Numbers

Foundational Concepts for Quantitative Research

Topic and Conceptualization

Measurement

Context

Working With Tables

Working With Charts and Visualizations

Comparison Values, Contrast Sizes, and Standards

Numbers, Comparisons, and Calculations

Distributions and Associations

Bias

Causality

Communicating Quantitative Research

The Role of Research Methods in Making Sense of Numbers

Filters

Exam 13: Uncertainty of Numeric Estimates

In a hypothesis test, a significance level of 0.05 was chosen. How would you interpret this value?

The sample mean of a variable is found to be 35.7. The true population mean of that variable was known to be 40.2. What is the sampling error of the variable?

Why does sampling from a population introduce uncertainty into the sample estimates?

The sample mean of a variable is 137.6, and is reported with an associated p value of 0.001. How could this p value be interpreted as?

Inferential statistics means reaching a conclusion about characteristics of a population based on sample data.

A "point estimate" is a summary statistic, such as the mean or proportion, of the population.

Describe the steps in developing a hypothesis test. Walk through these steps with an example.

Introduction to Making Sense of Numbers

Foundational Concepts for Quantitative Research

Topic and Conceptualization

Measurement

Context

Working With Tables

Working With Charts and Visualizations

Comparison Values, Contrast Sizes, and Standards

Numbers, Comparisons, and Calculations

Distributions and Associations

Bias

Causality

Communicating Quantitative Research

The Role of Research Methods in Making Sense of Numbers

Filters