r they related?
Predictions
Accepting Rejection
T-test
Misc
100

symbolized by the letter r this statistic is used to describe the relationship between 2 variables.

Pearsons correlation 

100

Equation for a line

Y=mX+b

100

Abbreviated H0 this hypothesis says there nothing to see here.

Null Hypothesis

100

Compares the means of two unrelated groups.

Independent t test

100

Describe the relationship r = 0.095

Trivial/Nothing

200

Also known as an indirect relationship this relationship is caused when x and Y vary in opposite directions.

Negative

200

Statistic that represents the standardized error of your prediction.

Standard Error of Estimate (SEE)

200

Opposite of the Null hypothesis

Alternative Hypothesis 

200

Compares means of a dependent variable between two paired groups or measurements.

dependent or paired t test.

200

Describe the relationship r = 0.783

Strong positive

300

Correlation coefficients tell us these two things about a relationship

size/strength and direction

300

In linear prediction the regression line is used to predict a unknown Y variable for a known _____ variable.

X

300

p = 0.0567 - Accept or reject?

Accept!

300

Measure of practical significance when comparing two means.

Effect size

300

Tests used after the main AVOVA turns up statistically significant.

post hoc

400

If you look enough you’ll find relationships. Type I error in correlation analysis is termed what?

Spurious correlation 

400

Calculated as the sd Y multiplied by the sqrt of 1-the r squared.

SEE

400

Reject Null when Null is correct, what type?

Type I

400

In addition to having normally distributed data, this is an assumption of the independent t test.

Equal variance OR homogeneity of variance  

400

ANOVA used to compare means of a single dependent variables between independent groups

One-Way ANOVA

500

Squaring your correlation coefficient created R2 statistic also known as

Coefficient of determination 

500

The difference between the prediction/regression line and the actual data is termed

Residual scores

500

Most common critical alpha in our field.

0.05 or 95%

500

p = 0.034 - Accept or Reject?

Reject!

500

ANOVA main effect is p > 0.05 your next step is?

Accept the Null / Do nothing

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