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MMW priv > Pearson r / Spearman rho > Flashcards

Pearson r / Spearman rho Flashcards

1
Q

Quantitatively expresses the extent to which two variables are related.

A

Pearson r

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2
Q

Measure of the strength and direction of association that exists between two variables measured as scale variables (ratio or interval).

A

Pearson r

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3
Q

T or F| Spearman rho tells us 2 things:
1. The direction of the relationsh Application in research…ip between the X & Y (positive or negative; linearity)

  1. The strength of the relationship between the X
    & Y (strong, moderate or weak)
A

F

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4
Q

T or F| Pearson’s r tells us 2 things:
1. The direction of the relationsh Application in research…ip between the X & Y (positive or negative; linearity)
2. The strength of the relationship between the X
& Y (strong, moderate or weak)

A

T

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5
Q

The main result of a correlation is called

A

Correlation Coefficient (r)

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6
Q

Correlation Coefficient (r) ranges from?

A

It ranges from -1 to +1.

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7
Q

T or F| In Pearson r, the closer r is to +1 or -1, the more closely the two variables are related.

A

T

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8
Q

If r = +1, then it denotes?

A

Perfect positive correlation

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9
Q

If r = -1, then it denotes?

A

Perfect negative correlation

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10
Q

r = 0 means?

A

There is no correlation

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11
Q

If r is positive, it means that as one variable gets larger the other gets ____

A

larger

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12
Q

If r is negative, it means that as one variable gets larger, the other gets ____

A

smaller

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13
Q

If r is negative, it means that as one variable gets larger, the other gets smaller -often called an

A

‘inverse correlation’

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14
Q

Very Weak

A

0.00-0.19

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15
Q

Weak

A

0.20-0.39

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16
Q

Moderate

A

0.40-0.59

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17
Q

Strong

A

0.60-0.79

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18
Q

Very strong

A

0.80-1.00

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19
Q

The variables must be either interval or ratio measurement

A

Pearson r

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20
Q

The data must be approximately normally distributed.

A

Pearson r

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21
Q

There is a linear relationship between the two variables.

A

Pearson r

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22
Q

Outliers are either kept to a minimum or are remove entirely.

A

Pearson r

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23
Q

There is homoscedasticity of the data.

A

Pearson r

24
Q

Test for normality: sample size is less than 50

A

Shapiro-Wilk test

25
Q

Test for normality: sample size is greater than 50

A

Kolmogorov-Smirnov test

26
Q

a test for homogeneity/ homoscedasticity of variances.

A

Levene’s test

27
Q

It is the nonparametric version of the Pearson product-moment correlation.

A

Spearman rho

28
Q

Spearman’s correlation coefficient p measures the strength and direction and association between _____________

A

two ranked variables

29
Q

parametric test of difference between two groups.

A

T test

30
Q

In t test the _____ are being compared between the two groups

A

Means

31
Q

Two types of t tests

A
  1. t-test for independent samples
  2. †-test for correlated/dependent samples
32
Q

test of difference between two independent groups

A

t-test for independent samples

33
Q

test of difference between correlated/dependent samples or one group of samples.

A

t-test for correlated samples

34
Q

Your dependent variable should be measured on a continuous scale (i.e., it is measured at the interval or ratio level).

A

T test

35
Q

In T test: _____ should consist of two categorical, independent groups.

A

Independent variable

36
Q

There should be no significant outliers.

A

T test

37
Q

In t test: ______ should be approximately normally distributed for each group of the independent variable

A

Dependent variable

38
Q

Also known as t-test for correlated samples

A

t-test for Dependent/Correlated Samples

39
Q

A test of difference between correlated samples or one group of samples

A

t-test for Dependent/Correlated Samples

40
Q

Your independent variable should consist of two categorical, ‘related groups” or “matched pairs”.

A

T test (dependent)

41
Q

indicates that the same subjects are present in both groups.

A

Related groups

42
Q

The distribution of the differences in the dependent variable between the two related groups should be approximately normally distributed.

A

t-test for Dependent/Correlated Samples

43
Q

Used when we want to predict the value of a variable based on the value of another variable.

A

Simple Linear Regression

44
Q

The variable we want to predict is

A

dependent variable (y)
Outcome variable

45
Q

The variable we are using to predict the other variable’s value is called

A

independent variable (x)
Predictor variable

46
Q

finds the best straight line for describing the relationship between two variables.

A

Simple linear regression

47
Q

Your data needs to show homoscedasticity.

A

Simple linear regression

48
Q

mathematical equation used to predict the values of one dependent variable from known values of one or more independent variables.

A

Regression equation

49
Q

y intercept

A

a

50
Q

Slope of the line

A

b

51
Q

extension of simple linear regression.

A

Multiple linear regression

52
Q

The multiple regression analysis is used to predict the dependent variable Y given the

A

Independent variables Xs

53
Q

used when we want to predict the value of a variable based on the value of two or more other variables.

A

Multiple Linear Regression

54
Q

Dependent variable also called as

A

target or criterion variable

55
Q

The variables we are using to predict the value of the dependent variable are called the independent variables or sometimes

A

predictor or explanatory variables

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