Suppose we wish to predict the profits, in hundreds of thousands of dollars, for companies that had sales, in hundreds ofthousands of dollars, of 500 units. We use statistical software to do the prediction and obtain the displayed output.St. dev. meanSales Predictpredict95% C.I.95% P.I.500-130.459.3(-248.5,-12.3)(-1066.4, 805.6)A random sample of 19 companies from the Forbes 500 list was selected, and the relationship between sales, in hundreds ofthousands of dollars, and profits, in hundreds of thousands of dollars, was investigated by regression. The simple linearregression model displayed was used: profits a + ß (sales), where the deviations were assumed to be independent andNormally distributed, with mean 0 and standard deviation o. This model was fit to the data using the method of leastsquares. The results displayed were obtained from statistical software.2= 0.662s = 466.2ParameterStd. err. ofestimateparameter est.Parameter-176.64461.160.0924980.0075A 95% confidence interval for the average profit of companies with 500 units of sales is:-1066 41n 805 6 A random sample of 19 companies from the Forbes 500 list was selected, and the relationship between sales, in hundreds ofthousands of dollars, and profits, in hundreds of thousands of dollars, was investigated by regression. The simple linearregression model displayed was used: profits= a + B (sales), where the deviations were assumed to be independent andNormally distributed, with mean 0 and standard deviation o. This model was fit to the data using the method of leastsquares. The results displayed were obtained from statistical software.2 = 0.662S= 466.2ParameterStd. err. ofParameterestimateparameter est.-176.64461.160.0924980.0075A 95% confidence interval for the average profit of companies with 500 units of sales is:-1066.4to 805.6.O -189.7 to -71.1.400.7 to 559.3.-248.5 to -12.3.delete

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Description: Suppose we wish to predict the profits, in hundreds of thousands of dollars, for companies that had sales, in hundreds ofthousands of dollars, of 500 units. We use statistical software to do the prediction and obtain the displayed output.St. dev. me

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Suppose we wish to predict the profits, in hundreds of thousands of dollars, for companies that had sales, in hundreds of thousands of dollars, of 500 units. We use statistical software to do the prediction and obtain the displayed output. St. dev. mean Sales Predict predict 95% C.I. 95% P.I. 500 -130.4 59.3 (-248.5,-12.3) (-1066.4, 805.6) A random sample of 19 companies from the Forbes 500 list was selected, and the relationship between sales, in hundreds of thousands of dollars, and profits, in hundreds of thousands of dollars, was investigated by regression. The simple linear regression model displayed was used: profits = a + B (sales), where the deviations were assumed to be independent and Normally distributed, with mean 0 and standard deviation o. This model was fit to the data using the method of least squares. The results displayed were obtained from statistical software. 2 = 0.662 s = 466.2 Parameter Std. err. of Parameter estimate parameter est. -176.644 61.16 0.092498 0.0075 A 95% contidence interval for the average profit of companies with 500 units of sales is: C-1066 Ato 805 6

Suppose we wish to predict the profits, in hundreds of thousands of dollars, for companies that had sales, in hundreds of thousands of dollars, of 500 units. We use statistical software to do the prediction and obtain the displayed output. St. dev. mean Sales Predict predict 95% C.I. 95% P.I. 500 -130.4 59.3 (-248.5,-12.3) (-1066.4, 805.6) A random sample of 19 companies from the Forbes 500 list was selected, and the relationship between sales, in hundreds of thousands of dollars, and profits, in hundreds of thousands of dollars, was investigated by regression. The simple linear regression model displayed was used: profits = a + B (sales), where the deviations were assumed to be independent and Normally distributed, with mean 0 and standard deviation o. This model was fit to the data using the method of least squares. The results displayed were obtained from statistical software. 2 = 0.662 s = 466.2 Parameter Std. err. of Parameter estimate parameter est. -176.644 61.16 0.092498 0.0075 A 95% contidence interval for the average profit of companies with 500 units of sales is: C-1066 Ato 805 6

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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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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Question

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Suppose we wish to predict the profits, in hundreds of thousands of dollars, for companies that had sales, in hundreds of
thousands of dollars, of 500 units. We use statistical software to do the prediction and obtain the displayed output.
St. dev. mean
Sales Predict
predict
95% C.I.
95% P.I.
500
-130.4
59.3
(-248.5,-12.3)
(-1066.4, 805.6)
A random sample of 19 companies from the Forbes 500 list was selected, and the relationship between sales, in hundreds of
thousands of dollars, and profits, in hundreds of thousands of dollars, was investigated by regression. The simple linear
regression model displayed was used: profits a + ß (sales), where the deviations were assumed to be independent and
Normally distributed, with mean 0 and standard deviation o. This model was fit to the data using the method of least
squares. The results displayed were obtained from statistical software.
2= 0.662
s = 466.2
Parameter
Std. err. of
estimate
parameter est.
Parameter
-176.644
61.16
0.092498
0.0075
A 95% confidence interval for the average profit of companies with 500 units of sales is:
-1066 41n 805 6

A random sample of 19 companies from the Forbes 500 list was selected, and the relationship between sales, in hundreds of
thousands of dollars, and profits, in hundreds of thousands of dollars, was investigated by regression. The simple linear
regression model displayed was used: profits
= a + B (sales), where the deviations were assumed to be independent and
Normally distributed, with mean 0 and standard deviation o. This model was fit to the data using the method of least
squares. The results displayed were obtained from statistical software.
2 = 0.662
S= 466.2
Parameter
Std. err. of
Parameter
estimate
parameter est.
-176.644
61.16
0.092498
0.0075
A 95% confidence interval for the average profit of companies with 500 units of sales is:
-1066.4to 805.6.
O -189.7 to -71.1.
400.7 to 559.3.
-248.5 to -12.3.
delete

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