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Question 1

What is the difference between parameters and statistics?

Answer 1

Parameters (𝜃) are conclusions about a population, while statistics (መ𝜃) are conclusions about a sample. Statistics are used as estimators of parameters.

Question 2

What is the purpose of inferential statistics?

Answer 2

Inferential statistics is used to make conclusions about a population based on data from a sample, using probability theory.

Question 3

What are the three types of hypotheses discussed in the text?

Answer 3

The three types of hypotheses are conceptual, operative, and statistical.

Question 4

What is a conceptual hypothesis?

Answer 4

A conceptual hypothesis is a direct statement that is easy to understand.

Question 5

What is an operational hypothesis?

Answer 5

An operational hypothesis is a hypothesis that is quantifiable, measurable, and analyzable and informs how the concepts will be measured.

Question 6

What is a statistical hypothesis?

Answer 6

A statistical hypothesis is formulated in terms of statistics or parameters and is precise and specific.

Question 7

What is a null hypothesis (H0)?

Answer 7

A null hypothesis (H0) is always stated in terms of equality, suggesting no effect, difference, or association. It is the opposite of the alternative hypothesis.

Question 8

What is an alternative hypothesis (H1)?

Answer 8

An alternative hypothesis (H1) is the opposite of the null hypothesis, suggesting an effect, difference, or association. It is based on the research hypothesis.

Question 9

What is a directional hypothesis?

Answer 9

A directional hypothesis predicts a particular direction of difference between populations.

Question 10

What is a non-directional hypothesis?

Answer 10

A non-directional hypothesis does not predict a particular direction of difference.

Question 11

What is the relationship between null and alternative hypotheses?

Answer 11

Null and alternative hypotheses are complementary and exclusive; accepting one entails rejecting the other.

Question 12

What does a one-tailed hypothesis test imply?

Answer 12

A one-tailed test is used with a directional hypothesis and tests for a difference in a specific direction.

Question 13

What does a two-tailed hypothesis test imply?

Answer 13

A two-tailed test is used with a non-directional hypothesis and tests for a difference in either direction.

Question 14

What is a p-value?

Answer 14

A p-value is the probability of finding a particular statistic by chance, given that the null hypothesis (H0) is true.

Question 15

What does a low p-value indicate?

Answer 15

A low p-value reduces the probability of the null hypothesis (H0) being true and indicates statistical significance.

Question 16

What is the typical significance level (α) used in hypothesis testing?

Answer 16

A typical significance level (α) is 0.05, meaning a probability of chance lower than 5% is considered significant.

Question 17

What is a Type I error?

Answer 17

A Type I error occurs when the null hypothesis (H0) is true but is rejected. It is a false positive.

Question 18

What is a Type II error?

Answer 18

A Type II error occurs when the null hypothesis (H0) is false but is accepted. It is a false negative.

Question 19

What is a confidence interval?

Answer 19

A confidence interval is an estimation of a range of values within which the true population parameter is likely to be found, with a high and known probability.

Question 20

What are parametric tests?

Answer 20

Parametric tests make assumptions about the parameters of the population distribution, often assuming the population data are normally distributed.

Question 21

What are non-parametric tests?

Answer 21

Non-parametric tests are ‘distribution-free’ and can be used for non-normal variables.

Question 22

When is a standard distribution used for hypothesis testing on means?

Answer 22

A standard (normal) distribution is used when the population variance or standard deviation is known.

Question 23

When is a Student’s t-distribution used?

Answer 23

A Student’s t-distribution is used when the population variance or standard deviation is unknown, or when two means are compared.

Question 24

What is ANOVA used for?

Answer 24

ANOVA (Analysis of Variance) is used to compare more than two means. It uses the Snedecor’s F statistic.

Question 25

What is the Chi-Square test used for?

Answer 25

The Chi-Square test is used to test associations between two categorical variables.

Question 26

What is the Pearson correlation test used for?

Answer 26

The Pearson correlation test is used to test the linear relationship between two quantitative variables.

Question 27

What is the general linear model?

Answer 27

The general linear model is a set of parametric analyses that aim to predict a variable based on one or more other variables, assuming a linear relationship.

Question 28

What is linear regression used for?

Answer 28

Linear regression is used to predict changes in a dependent variable (Y) from changes in an independent variable (X).

Question 29

What is the coefficient of determination (R²)?

Answer 29

The coefficient of determination (R²) indicates the proportion of the variability in the dependent variable (Y) that can be explained by the independent variable(s) (X). It is calculated as the square of the correlation coefficient.

Question 30

What is the purpose of hypothesis testing in the regression model?

Answer 30

Hypothesis testing in the regression model is used to determine if the model provides a good degree of prediction of the result variable and to determine if the independent variable is a significant predictor of the dependent variable.