stats 5

Question 1

hypothesis

Answer 1

a testable statement predicting a relationship or effect between variables, often framed as an expectation of what will happen

Question 2

null hypothesis

Answer 2

a specific type of hypothesis that assumes no effect or no difference between variables and serves as a baseline to test against

Question 3

The null hypothesis gives a

Answer 3

counterfactual

Question 4

Counterfactual

Answer 4

an alternative scenario or condition that contrasts with the proposed effect or relationship in the hypothesis, effectively serving as the null hypothesis which assumes no effect or difference

Question 5

Researchers need a null hypothesis to provide a

Answer 5

baseline or default position that allows us to test and determine whether observed data provides sufficient evidence to support a proposed effect or relationship

Question 6

it is important to develop a corresponding - for each
hypothesis for purposes of -

Answer 6

null hypothesis, hypothesis testing

Question 7

Hypothesis testing

Answer 7

a statistical method used to determine whether there is enough evidence in a sample of data to support a specific claim or hypothesis about a population

Question 8

Hypothesis testing determines if your sample data provides enough evidence to

Answer 8

reject a null hypothesis in favor of an
alternative hypothesis

Question 9

first step of hypothesis testing

Answer 9

state the null hypothesis (e.g., no difference between the sample mean and a population mean) and the
alternative hypothesis (e.g., a difference exists)

Question 10

second step of hypothesis testing

Answer 10

set a critical value

Question 11

Critical value

Answer 11

a predetermined threshold derived from a particular statistical distribution used to conduct a statistical test

Question 12

Each critical value has an associated

Answer 12

significance level

Question 13

Significance level

Answer 13

the probability of rejecting the null hypothesis when its actually true, representing the threshold for statistical significance.

Question 14

third step of hypothesis testing

Answer 14

calculate a test statistic from your sample data

Question 15

Test statistic

Answer 15

a value calculated by:
* identifying the sample statistic (e.g., the mean),
* determining its standard error (e.g. standard error of the mean),
and
* using a specific formula to assess how far the sample result
deviates from the null hypothesis

Question 16

Different hypothesis tests are interested in different sample statistics.
For example:

Answer 16

• the t-Test sample statistic is the sample mean,
• the Chi-Squared test sample statistic is the observed frequency in
  a contingency table, and
• the ANOVA sample statistic is the sample mean squares.

Question 17

fourth step of hypothesis testing

Answer 17

After calculating the test statistic from your sample data, you compare it to the critical value.

Question 18

fifth step of hypothesis testing

Answer 18

You then find the p-value of your data.

Question 19

p-value

Answer 19

the probability of obtaining a test statistic as extreme as, or more extreme than, the one observed, assuming the null hypothesis is true

Question 20

p-values are a probability, so they range from

Answer 20

0 to 1 (0-100%)

Question 21

sixth step of hypothesis testing

Answer 21

compare p value of your data to the critical values significance level (a) to determine whether the result is statistically significant.

Question 22

a p val that is smaller than the significance value (a) suggests that such a result is unlikely under the

Answer 22

null hypothesis, leading you to reject it in favor of the alternative hypothesis

Question 23

a p val that is larger than the significance value (a) suggests that such a result is likely under the

Answer 23

null hypothesis, leading you to reject it in favor of the alternative hypothesis

Question 24

In the social sciences, the standard p-value threshold is

Answer 24

p = 0.05.

Question 25

When the p-value is adequately small (e.g., p < 0.05), the findings are considered

Answer 25

statistically significant

Question 26

Statistical significance

Answer 26

an indication that an observed effect or relationship in the data is unlikely to have occurred by random chance alone. (assuming the null hypothesis is true and the study is repeated an infinite number of times by drawing random samples from the same population, less than 5% of these results will be more extreme than the current result.)

Question 27

When a result is statistically significant, that does not mean that

Answer 27

the alternative hypothesis is proven to be true. It just means you can reject the null hypothesis

Question 28

Statistical significance really just means that

Answer 28

we are not likely to see the relationship between our variables by chance alone

Question 29

Chi-squared test of tabular association

Answer 29

a statistical test that evaluates whether observed categorical data align with the expected frequencies based on a specific hypothesis

Question 30

Bivariate analysis

Answer 30

the analysis or examination of the relationship between two variables, such as an independent variable and a dependent variable

Question 31

Categorical variable

Answer 31

a type of variable that represents distinct categories or groups without any inherent numerical value or order, such as gender, color, or type of car. (have 2 or more categories. * Categorical variables with 2 categories are often called binary, dummy, or dichotomous variables.)

Question 32

1. To define your null hypothesis, first define your

Answer 32

research question

Question 33

To define your null hypothesis,

Answer 33

write out both your null and alternative hypotheses

Question 34

To define your null hypothesis,

Answer 34

think about what hypothesis test you need

Question 35

To define your null hypothesis, next making a

Answer 35

contingency table (The independent variable should go in the columns. * The dependent variable should go in the rows.)

Question 36

Contingency table

Answer 36

a matrix that displays the frequency distribution of two categorical variables, showing how their values intersect

Question 37

To define your null hypothesis, next think about

Answer 37

what the data would look like if the null hypothesis were to be true, If the null hypothesis is true, we would expect there to be no difference in turnout by party affiliation

Question 38

Define your null hypotheses

Answer 38

there is no relationship between partisan affiliation and voter turnout.

Question 39

next, identify the

Answer 39

critical value

Question 40

we need 2 pieces of information to define a critical value in a chi-squared test of tabular association

Answer 40

- a value for alpha (a) and - the degrees of freedom (df)

Question 41

Degrees of freedom

Answer 41

the number of independent values or quantities that can vary in a statistical calculation, typically indicating the number of values that are free to vary after certain constraints are applied

Question 42

The shape of the Chi-square distribution depends on the

Answer 42

degrees of freedom!

Question 43

3. Calculate a test statistic from the

Answer 43

sample data

Question 44

4. compare test statistic from your sample data to the

Answer 44

critical value

Question 45

5. Find the - of the data

Answer 45

p-value