Stats 9.1 & 9.2
Match this description with a description below. Slope
m
Correlation Coefficient
Σx = Sum of x values. Σy = Sum of y values. Find product of x and y values. (multiply them) Σxy = Sum of products. Square each of the x values. Σx² = Sum of the squared x values. Square each of the y values. Σy² = Sum of the square u values. n = number of data pairs.
Given a set of data and a corresponding regression line, describe all values of x that provide meaningful predictions for y.
Prediction values are meaningful only for x-values in (or close to) the range of the original data.
The scatter plot of a paired data set is shown. Determine whether there is a perfect positive linear correlation, a strong positive linear correlation, a perfect negative linear correlation, a strong negative linear correlation, or no linear correlation between the variables.
no linear correlation.
Which value of r indicates a stronger correlation: r = 0.807 or r = -0.856? Explain your reasoning.
r = -0.856 represents a stronger correlation because |-0.856| > |0.807|.
Discuss the difference between r and p.
r represents the sample correlation coefficient. p represents the population correlation coefficient.
Linear Regression T-test
STAT, 1. Edit and put x's in list 1 and y's in list 2. Then, select STAT and arrow over to highlight the TESTS menu for hypothesis testing. Scroll down and select LinReg T-Test (one of the last options in the TESTS menu). On this screen you will only need to select the symbol for the type of test you are doing, which should be the not equal, then Calculate.
Correlation Coefficient
STAT, choose 1. Edit, then put x's in list 1 and y's in list 2. Then, STAT, arrow over to highlight CALC menu. Choose 4. LinReg(ax + b), on this screen you only need to scroll down and select Calculate.
Two variables have a positive linear correlation. Does the dependent variable increase or decrease as the independent variable increases?
The dependent variable increases.
Identify the explanatory variable and the response variable. A golfer wants to determine if the type of equipment used every year can be used to predict the amount of improvement in his game.
The explanatory variable is the type of equipment used. The response variable is the amount of improvement in his game.
What does it mean to say "correlation does not imply causation"?
The fact that two variables are strongly correlated does not in itself imply a cause-and-effect relationship between the variables.
Describe the range of values for the correlation coefficient.
The range of values for the correlation coefficient is -1 to 1, inclusive.
Two variables have a positive linear correlation. Is the slope of the regression line for the variables positive or negative?
The slope is positive. As the independent variable increases the dependent variable also tends to increase.Th
Slope y-intercept The y value of a data point corresponding to xi the y value for a point on the regression line corresponding to xi
m b yi ∧yi
Critical values
n - 2 T distribution chart
