In order to determine the relationship between the number of units sold of a company's product (yy) in 9 cities with their major competitor's price (x1x1) in dollars, and the number of stores (x2x2) the competitor has in each city, the following data were collected. Units sold Competitor Price Competitor Stores 510 35 5 600 44 3 600 41 2 600 40 2 650 45 1 590 40 2 600 41 1 540 40 5 590 40 2 Generate a linear multiple regression output for the data. a) Report the regression coefficients accurate to 3 decimal places: ˆyy^= + x1 + x2 b) Report the coefficient of determination accurate to 3 decimal places: R2=
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.
In order to determine the relationship between the number of units sold of a company's product (yy) in 9 cities with their major competitor's price (x1x1) in dollars, and the number of stores (x2x2) the competitor has in each city, the following data were collected.
| Units sold | Competitor Price |
Competitor Stores |
|---|---|---|
| 510 | 35 | 5 |
| 600 | 44 | 3 |
| 600 | 41 | 2 |
| 600 | 40 | 2 |
| 650 | 45 | 1 |
| 590 | 40 | 2 |
| 600 | 41 | 1 |
| 540 | 40 | 5 |
| 590 | 40 | 2 |
Generate a linear multiple regression output for the data.
a) Report the regression coefficients accurate to 3 decimal places:
ˆyy^= + x1 + x2
b) Report the coefficient of determination accurate to 3 decimal places:
R2=
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