Pearson r / Spearman rho Flashcards
Quantitatively expresses the extent to which two variables are related.
Pearson r
Measure of the strength and direction of association that exists between two variables measured as scale variables (ratio or interval).
Pearson r
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)
- The strength of the relationship between the X
& Y (strong, moderate or weak)
F
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)
T
The main result of a correlation is called
Correlation Coefficient (r)
Correlation Coefficient (r) ranges from?
It ranges from -1 to +1.
T or F| In Pearson r, the closer r is to +1 or -1, the more closely the two variables are related.
T
If r = +1, then it denotes?
Perfect positive correlation
If r = -1, then it denotes?
Perfect negative correlation
r = 0 means?
There is no correlation
If r is positive, it means that as one variable gets larger the other gets ____
larger
If r is negative, it means that as one variable gets larger, the other gets ____
smaller
If r is negative, it means that as one variable gets larger, the other gets smaller -often called an
‘inverse correlation’
Very Weak
0.00-0.19
Weak
0.20-0.39
Moderate
0.40-0.59
Strong
0.60-0.79
Very strong
0.80-1.00
The variables must be either interval or ratio measurement
Pearson r
The data must be approximately normally distributed.
Pearson r
There is a linear relationship between the two variables.
Pearson r
Outliers are either kept to a minimum or are remove entirely.
Pearson r
There is homoscedasticity of the data.
Pearson r
Test for normality: sample size is less than 50
Shapiro-Wilk test
Test for normality: sample size is greater than 50
Kolmogorov-Smirnov test
a test for homogeneity/ homoscedasticity of variances.
Levene’s test
It is the nonparametric version of the Pearson product-moment correlation.
Spearman rho
Spearman’s correlation coefficient p measures the strength and direction and association between _____________
two ranked variables
parametric test of difference between two groups.
T test
In t test the _____ are being compared between the two groups
Means
Two types of t tests
- t-test for independent samples
- †-test for correlated/dependent samples
test of difference between two independent groups
t-test for independent samples
test of difference between correlated/dependent samples or one group of samples.
t-test for correlated samples
Your dependent variable should be measured on a continuous scale (i.e., it is measured at the interval or ratio level).
T test
In T test: _____ should consist of two categorical, independent groups.
Independent variable
There should be no significant outliers.
T test
In t test: ______ should be approximately normally distributed for each group of the independent variable
Dependent variable
Also known as t-test for correlated samples
t-test for Dependent/Correlated Samples
A test of difference between correlated samples or one group of samples
t-test for Dependent/Correlated Samples
Your independent variable should consist of two categorical, ‘related groups” or “matched pairs”.
T test (dependent)
indicates that the same subjects are present in both groups.
Related groups
The distribution of the differences in the dependent variable between the two related groups should be approximately normally distributed.
t-test for Dependent/Correlated Samples
Used when we want to predict the value of a variable based on the value of another variable.
Simple Linear Regression
The variable we want to predict is
dependent variable (y)
Outcome variable
The variable we are using to predict the other variable’s value is called
independent variable (x)
Predictor variable
finds the best straight line for describing the relationship between two variables.
Simple linear regression
Your data needs to show homoscedasticity.
Simple linear regression
mathematical equation used to predict the values of one dependent variable from known values of one or more independent variables.
Regression equation
y intercept
a
Slope of the line
b
extension of simple linear regression.
Multiple linear regression
The multiple regression analysis is used to predict the dependent variable Y given the
Independent variables Xs
used when we want to predict the value of a variable based on the value of two or more other variables.
Multiple Linear Regression
Dependent variable also called as
target or criterion variable
The variables we are using to predict the value of the dependent variable are called the independent variables or sometimes
predictor or explanatory variables
