Chapter 13 Flashcards
correlation analysis vs and regression analysis?
From correlation we can only get an index describing the linear relationship between two variables; in regression we can predict the relationship between more than two variables and can use it to identify which variables x can predict the outcome variable y.
What is the range for the correlation coefficient?
The Pearson correlation coefficient, r, can take a range of values from +1 to -1. A value of 0 indicates that there is no association between the two variables. A value greater than 0 indicates a positive association; that is, as the value of one variable increases, so does the value of the other variable.
How about coefficient of determination?
The coefficient of determination is the square of the correlation (r) between predicted y scores and actual y scores; thus, it ranges from 0 to 1.
How does one obtain a confidence interval?
Write down the phenomenon you’d like to test
Select a sample from your chosen population.
Calculate your sample mean and sample standard deviation.
Choose your desired confidence level
Calculate your margin of error.
State your confidence interval
Univariate analysis
Univariate analyses provide insights about the data while multivariate analyses can often provide further illumination of those insights
multivariate analysis
Multivariate analyses allow researchers a closer look at their data than is possible with univariate analyses
Cross tabulation
A multivariate technique used for studying the relationship between two or more categorical variables. The technique considers the joint distribution of sample elements across variables.
The content of the “Cells” can be controlled
The default is “actual observation”
You should use “row” or “Column” percentages or both
Pearson Chi-square test of independence
Pearson chi-square (χ2) test of independence
A commonly used statistic for testing the null hypothesis that categorical variables are independent of one another
Cramer’s V
Cramer’s V
A statistic used to measure the strength of relationship between categorical variables
Pearson correlation coefficient
A statistic that indicates the degree of linear association between two continuous variables
The correlation coefficient can range from -1 (inverse relationship) to +1 (direct relationship)
Note: Correlation ≠ Causation; Correlation = Relationship Examples Relationship between number of times exercising with weights and number of times exercising in a fitness class during the month
simple regression
A statistical technique used to derive an equation that relates a single continuous dependent variable to a single independent variable.
One dependent variable (e.g. Sales)
One independent variable (e.g. Price)
multiple regression
A statistical technique used to derive an equation that relates a single continuous dependent variable to two or more independent variables.
One dependent variable
More than one independent variables
Regression Analysis
A statistical technique used to derive an equation that relates a single continuous dependent variable to a single independent variable
