For the five days from April 19-23, Sam counted the number of cups of caffeinated drinks he consumed (X) and the number of non-caffeinated drinks he consumed (Y). The following were the raw data for X and Y: Date X # caffeinated drinks Y = # non-caffeinated drinks %3! April 19 April 20 3 4 April 21 April 22 April 23 3 10 2 The mean and standard deviation for X (i.e., # of caffeinated drinks Sam drank) and the mean and standard deviation for Y (i.e., # of non-caffeinated drinks Sam drank) are: meanx = 6 meany = 3.6 %3D stdDevx = 2.45 stdDevy = 1.9 %3D Answer the following questions using the correlation reading: 1. Calculate the Pearson product-moment correlation coefficient, r, between X and Y for Sam. 2. Is this a positive or a negative correlation? 3. Is this a strong or a weak correlation?
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.
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