Research methods/stats - Inferential stats

Question 1

In probability sampling, when the sample value of interest is a mean, the appropriate sampling distribution is a _____.

Answer 1

sampling distribution of means.

Question 2

Inferential statistics are used to determine if the results of a research study are due to the ________ or to _______.

Answer 2

effects of an independent variable on a dependent variable, sampling error

Question 3

In inferential statistics, the _____ is used to estimate the characteristics of the sampling distribution (i.e., estimate a sampling distribution of means).

Answer 3

the central limit theorem

Question 4

Three assumptions of the central limit theorem in inferential statistics?

Answer 4

(a) The sampling distribution will increasingly approach a normal shape as the sample size increases, regardless of the shape of the population distribution of scores.
(b) The mean of the sampling distribution of means will be equal to the population mean.
(c) The standard deviation of the sampling distribution – which is referred to as the standard error of means – will be equal to the population standard deviation divided by the square root of the sample size.

Question 5

In inferential stats, the ____ hypothesis is stated in a way that indicates that the independent variable does not have an effect on the dependent variable, while the ______ hypothesis is stated in a way that indicates that the independent variable does have an effect on the dependent variable.

Answer 5

null, alternative

Question 6

In inferential stats, rejecting a null hypothesis when it is true is referred to as a _____ error.

Answer 6

Type 1

Question 7

In inferential stats, the probability of making a Type I error is equal to ____, aka the level of significance (for an effect). A .05 value of ____ is equal to a 5% chance of making a type I error, while a .01 value is equal to a 1% chance.

Answer 7

alpha (all blanks)

Question 8

In inferential stats, accepting a null hypothesis when it is false is referred to as a _____ error.

Answer 8

Type II

Question 9

The probability of making a Type II error in inferential stats is equal to beta, which is not set by the researcher but can be reduced by increasing ______.

Answer 9

statistical power

Question 10

Statistical power refers to the ability to _____ a ______ hypothesis

Answer 10

reject, false null

Question 11

The larger the size of ______, the greater the statistical power, despite _____ typically being set low to avoid a type I error.

Answer 11

alpha (all)

Question 12

In inferential stats, the size of the _____ of the _____ variable on the _____ variable is one factor that influences statistical power.

Answer 12

effect, independent, dependent

Question 13

One factor that influences statistical power is the ____ of the sample

Answer 13

size

Question 14

One factor that influences statistical power is the type of inferential test that’s used to analyze the data. ______ tests are better than ______ tests, but they can be used only when the data to be analyzed are interval or ratio data and certain assumptions are met.

Answer 14

parametric, nonparametric

Question 15

T-tests and analysis of variance (ANOVA) tests are _____ tests used to analyze ratio or interval data, whereas a chi-square analysis is a _____ test because it analyzes nominal data.

Answer 15

parametric, nonparametric

Question 16

One factor influencing statistical power is population _______. Populations that have more ______ with regard to status or scores on the dependent variable will lead to higher power.

Answer 16

Homogeneity (both)

Question 17

In contrast to frequentist (aka classical) stats, which involves drawing conclusions about a parameter (e.g., mean, variance, regression coefficient) from data collected in a current study, _____ analysis involves a knowledge-building process in which updated knowledge about a parameter is derived by combining information from data collected in a current study with previous information about that parameter.

Answer 17

Bayesian

Question 18

_____ statistics defines probability as the frequency of times a parameter is expected to occur with repeated measurement when the conditions of measurement are held constant. In contrast, _____ statistics adopts a subjective approach and defines probability as the degree of belief (certainty) about the occurrence of the parameter.

Answer 18

Frequentist or classical, Bayesian

Question 19

Frequentist or classical stats use confidence intervals, whereas Bayesian stats use ________ intervals. For a 95% confidence interval, with different samples from the same population, 95% of the confidence intervals would contain the true mean. With _____ intervals, the interpretation would be there is a 95% chance that the true population mean is within the interval.

Answer 19

credibility

Question 20

In Bayesian stats, the _____ is the probability distribution for a parameter before collecting new data. It is chosen by the researcher and is usually based on previous research.

Answer 20

prior

Question 21

In Bayesian stats, the ______ is the probability distribution derived from data collected in the current study.

Answer 21

likelihood function

Question 22

In Bayesian stats, the _____ is the updated probability distribution for the parameter that is obtained by synthesizing the prior distribution and likelihood function. It is used to draw conclusions about the study’s hypothesis and may become the prior in subsequent research.

Answer 22

posterior