Stats practice

Do you have a true Independent variable?

Is yes, use Regression analysis

Type of statistic to predict group membership

Logistic regression

T-test

Looks at the differences between two groups The IV must have ONLY two groups

The mathematical average

Mean

The center value

Median

The most commonly occurring value

Mode

MANOVA

Same as ANOVA but you can study two or more related DVs while controlling for the correlation between the DV

MANCOVA

Same as MANOVA but adds controls of one or more covariates that may effect the influence of DV

Is this study interested in INTERVENTIONS (group differences)?

T-test, anova, manova, chi square

ANOVA

Tests the significance of group differences between two or more groups (but doesn't tell you what the difference is)

Several ways to refer to the significance level of a test:

The finding is significant at the 0.05 level. The confidence level is 95 percent. The Type I error rate is 0.05. The alpha level is 0.05. α = 0.05. There is a 1 in 20 chance of obtaining this result (or one more extreme). The area of the region of rejection is 0.05. The p‐value is 0.05. p = 0.05.

The width of the confidence interval is related to the confidence level, standard error, and n such that the following are true:

The higher the percentage of confidence desired, the wider the confidence interval. The larger the standard error, the wider the confidence interval. The larger the n, the smaller the standard error, and so the narrower the confidence interval.

Types of Statistics for Group Differences

chi-sqaure t-test Anova ancova Manova Mancova

A Type I error can occur when the null hypothesis is

correct.

If the significance level, α, is increased then the chance of a Type II error will

decrease

If the significance level, α, is increased then the power will

increase

If the significance level, α, is increased, then the chance of a Type I error will

increase

A Type II error can occur when the null hypothesis

is incorrect

A null hypothesis should be rejected when the p‐value is:

less than the significance level.

The conditional probability of obtaining the sample statistic, or one more extreme, given that the null hypothesis is true is called the:

p-value

ANCOVA

same as ANOVA but adds control of one or more covariates that may influence DV

Bottles of water have a label stating that the volume is 12 oz. A consumer group suspects the bottles are under‐filled and plans to conduct a test. A Type I error in this situation would mean

the consumer group concludes the bottles have less than 12 oz. when the mean actually is 12 oz.

The smaller the significance level p:

the more stringent the test and the greater the likelihood that the conclusion is correct

Selecting the significance level α will determine

the probability of a Type I error

What kind of statistic do you use to test for differences in the means of groups?

two groups: t -test more than two groups: ANOVA

The power of a test can be increased by

using a larger sample size

Which is not a typical significance level?

.25

Standard Deviation

1. How much scores deviate from the mean 2. Is the square root of the variance 3. is the most commonly used measure of spread

Selecting the significance level α is based on:

1. desired strength of evidence against the null hypothesis. 2. an acceptable probability of a Type I error.

Types of Statistics to determine Degree of Relationship

Bivariate correlation Multiple regression Path analysis

Chi Square

Compares observed frequencies to expected frequencies.

Nominal or ordinal data (discrete or categorical)

Use chi square

Is this study interested in description (association)?

Use correlations, factor analysis, and path analysis

IS this study interested in explanation or prediction?

Use: regression, logistic regression, discriminant analysis

A measure of how spread out a distribution is

Variance

A type II error occurs when

a null hypothesis is not rejected but should be rejected. Saying there are no differences or effects when there actually are.

A type I error occurs when

a null hypothesis is rejected but should not be rejected. Saying there is an effect/difference when there is actually not a statistically sig effect or difference

All other things being equal:

a smaller confidence interval is always more desirable than a larger one because a smaller interval means the population parameter can be estimated more accurately.