Inappropriate use of independent-samples t-test
Comparing students’ attitudes changes between the start and end of their degree.
Represents the researcher’s prediction or expectation.
Alternative hypothesis
Assesses the means of two independent groups.
T-test
Requirement for using a t-test
The sample must be normally distributed.
Correlation coefficient close to one
Strong linear relationship between the two variables.
APA format reporting for Pearson’s product-moment
Use “r”
Measure the strength and direction of a relationship between variables.
Purpose of correlation analysis
Maximum possible value for a correlation coefficient
1.00
Correlation coefficient of -1
Perfect negative relationship between variables
Expected correlation between a child’s age and vocabulary
Positive
Important statistics when interpreting an independent sample t-test
Descriptive statistics
significance level
t-value
Sequence of steps in hypothesis testing
Formulate hypotheses
collect data
analyze data
draw conclusions
Ex. of a categorical variable
Gender
age group
hair color
marital status
The probability of finding statistical significance.
P-value
Identifying significant differences in independent t-test output
Look at the p-value
Interpretation of a Pearson test statistic of .876 with P < 0.01:
Significant, strong, positive relationship
Purpose of statistical tests
To test the null hypothesis
Types of t-tests
One-sample t-test
independent two-sample t-test
paired sample t-test
Used when there are more than two groups.
ANOVA
High standard deviation in a graph
Indicates data is dispersed over a wide range of values.
Low standard deviation in a graph
Looks closely clustered around the mean
Describes the direction and magnitude of a relationship between two variables.
Correlation
One-tailed test appropriateness
Identified by the alternative hypothesis.
Pearson’s product-moment relationships:
Assess only linear relationships.
