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Assumptions in Statistical Tests: Chi-Square, t-Test, ANOVA, Regression, Quizzes of Statistics

The assumptions required for various statistical tests, including chi-square goodness of fit, student's t-test, t-test/anova, multiple regression, and regression/correlation. These assumptions include independent data collection, homoscedascity, normal distribution, and linearity.

Typology: Quizzes

2016/2017

Uploaded on 12/17/2017

koofers-user-lx1
koofers-user-lx1 🇺🇸

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TERM 1
Assumptions of Chi^2 Goodness of Fit,
Independence and Exact Goodness of Fit
DEFINITION 1
- Independent Data Collection
TERM 2
Assumptions of Student's t-Test
DEFINITION 2
- Homoscedascity- Independent Data Collection- Normal
Distribution
TERM 3
T-test/ANOVA
DEFINITION 3
- Independent Data Collection
TERM 4
Assumptions of Multiple Regression
DEFINITION 4
- No Multicolinearity: Variables are not correlated with one
another- Homoscedascity- Independent Data Collection-
Normal Distribution- Linearity
TERM 5
Assumptions of Regression/Correlation
DEFINITION 5
- Homoscedascity- Normal Distribution- Linearity (variables
are linearly related to each other)- Independent Data
Collection
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TERM 1

Assumptions of Chi^2 Goodness of Fit,

Independence and Exact Goodness of Fit

DEFINITION 1

- Independent Data Collection

TERM 2

Assumptions of Student's t-Test

DEFINITION 2

- Homoscedascity- Independent Data Collection- Normal

Distribution

TERM 3

T-test/ANOVA

DEFINITION 3

- Independent Data Collection

TERM 4

Assumptions of Multiple Regression

DEFINITION 4

- No Multicolinearity: Variables are not correlated with one

another- Homoscedascity- Independent Data Collection-

Normal Distribution- Linearity

TERM 5

Assumptions of Regression/Correlation

DEFINITION 5

- Homoscedascity- Normal Distribution- Linearity (variables

are linearly related to each other)- Independent Data

Collection