Use the given data set to complete parts (a) through (c) below. (Use a = 0.05.) 10 9.14 6.14 A Click here to view a table of critical values for the correlation coefficient. OA. OB. Oc. OD. 2 16 b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r= (Round to three decimal places needed) Using the linear correlation coefficient found in the previous step, determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. Choose the correct answer below. O A. There is insufficient evidence to support the claim of a linear correlation between the two variables. OB. There is sufficient evidence to support the claim of a linear correlation between the two variables. OC. There is sufficient evidence to support the claim of a nonlinear correlation between the two variables. OD. There is insufficient evidence to support the claim of a nonlinear correlation between the two variables. c. Identify the feature of the data that would be missed if part (b) was completed without constructing the scatterplot. Choose the correct answer below. O A. The scatterplot reveals a distinct pattern that is a straight-line pattern with positive slope. OB. The scatterplot reveals a distinct pattern that is a straight-line pattern with negative slope. OC. The scatterplot does not reveal a distinct pattern. OD. The scatterplot reveals a distinct pattern that is not a straight-line pattem.
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
Use the given data set to complete parts (a) through (c) below. (Use
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