Chapter 9 (One Sample t Test) & Chapter 10 (Correlation) Flashcards
What does one- sample t test determine?
Whether or not the sample mean is statistically different (statistically significant) from a population mean.
Z test
Tests the null hypothesis in relation to the following given that the population’s standard deviation is known and the data belongs to normal distribution:
T-test
Test the null hypothesis in relation to the following given the population standard deviation is unknown, data belongs to normal distribution, and the sample size is small (size less than 30)
Why are t-distributions more flatter and spread out?
The tails of a t distribution are thicker, which reflects the greater variability in values resulting from not knowing the population variance
What happens to shape of t distribution as df increase?
Becomes closer to a normal distribution
Assumptions for One Sample t Test
1) The values in the sample must consist of independent observations
2) The population sampled must be normal (your sample data is used to represent this)
Three ways to check normality
1) are mean and median the same or very similar
2) shape of graph
3) normality test: p<a = normality is not met
p>a= normality is met
Coeffient of Determination (r^2)
Measures the proportion of variability in one variable that can be determined from the relationship with the other variable
Types of Correlation
1) Pearson
2) Spearmen Rho
3) Kendall’s Tau
4) Point biserial
5) Biserial
6) Phi
Spearmen Rho
skewed, ordinal data, non-linear relationships
Kendall’s Tau
ordinal data, better than sperman for small samples,
Point biserial
continuous variable and natural binary variable
Biserial
continuous variable and binary variable with underlying continuity
Phi
Two binary variables
Covariability
Degree to which x and y vary together
