We are given a linear regression that gives us an equation on the relationship of Quantity on Total Cost. As stated in the project, the regression data is very good with a relatively high R2, significant F, and t-values but we can’t use this model to estimate plant size. When we perform a simple eye test on the residual plot for Q a trend seems to form from positive to negative and back to positive. When we also fit a linear trend line to the normal probability plot we can also see a pattern. This may indicate that the errors are not normally distributed; the effect is an increase in the tendency to reject the null hypothesis (type 1 error). But the easiest way to see that the model is not the best for this data is when you assign trend lines to the data.

Linear fit is ok, but you can see that the data is too spread out.

Polynomial to the 3rd order is a better fit, but we can do better.

Polynomial to the 2nd order is the best fit, the data is pretty “snug”.

Attached you will find the regression analysis for all three models with the 2nd order model having the best results with a high R2 and a very significant F with a better looking normal probability plot and Q/Q2 residuals distributed more randomly. The model that is produced with standard errors in parenthesis is: TC =| 347.9484| - 12.4285Q| + 0.356795Q2|

| (77.19129)| (5.50019)| (0.089795)|
| R2 = 0.7970| SEE = 58.9922| F = 52.9924|
| | | |

ATC =| 347.9484/Q| -12.4285| + 0.356795Q|
Both Q and Q2 are significant at an Alpha of .05 with the entire model being highly significant, if you conclude one or more of the coefficients is not equal to zero the probability of being wrong is less than 0.000000000449. This function is statistically better and can actually be used to estimate plant size.

...
Unit 5 – RegressionAnalysis
Mikeja R. Cherry
American InterContinental University
Abstract
In this brief, I will demonstrate selected perceptions of the company Nordstrom, Inc., a retailer that specializes in fashion apparel with over 12 million dollars in sales last year. I will research, review, and analyze perceptions of the company, create graphs to show qualitative and quantitative analysis, and provide a summary of my findings....

...REGRESSIONANALYSIS
Correlation only indicates the degree and direction of relationship between two variables. It does not, necessarily connote a cause-effect relationship. Even when there are grounds to believe the causal relationship exits, correlation does not tell us which variable is the cause and which, the effect. For example, the demand for a commodity and its price will generally be found to be correlated, but the question whether demand depends on...

...cannot consult the regression R2 because
(a) ln(Y) may be negative for 0 < Y < 1.
(b) the TSS are not measured in the same units between the two models.
(c) the slope no longer indicates the effect of a unit change of X on Y in the log-linear
model.
(d) the regression R2 can be greater than one in the second model.
1
(v) The exponential function
(a) is the inverse of the natural logarithm function.
(b) does not play an important role...

...Quantitative Methods Project
RegressionAnalysis for the pricing of players in the
Indian Premier League
Executive Summary
The selling price of players at IPL auction is affected by more than one factor. Most of these factors affect each other and still others impact the selling price only indirectly. The challenge of performing a multiple...

...RegressionAnalysis (Tom’s Used Mustangs)
Irving Campus
GM 533: Applied Managerial Statistics
04/19/2012
Memo
To:
From:
Date: April 19st, 2012
Re: Statistic Analysis on price settings
Various hypothesis tests were compared as well as several multiple regressions in order to identify the factors that would manipulate the selling price of Ford Mustangs. The data being used contains observations on 35 used Mustangs...

...RegressionAnalysis Exercises
1- A farmer wanted to find the relationship between the amount of fertilizer used and the yield of corn. He selected seven acres of his land on which he used different amounts of fertilizer to grow corn. The following table gives the amount (in pounds) of fertilizer used and the yield (in bushels) of corn for each of the seven acres.
|Fertilizer Used |Yield of Corn...

...l
RegressionAnalysis
Basic Concepts & Methodology
1. Introduction
Regressionanalysis is by far the most popular technique in business and economics for
seeking to explain variations in some quantity in terms of variations in other quantities, or to
develop forecasts of the future based on data from the past. For example, suppose we are
interested in the monthly sales of retail outlets across the UK. An initial data...

...
Mortality Rates
RegressionAnalysis of Multiple Variables
Neil Bhatt
993569302
Sta 108 P. Burman
11 total pages
The question being posed in this experiment is to understand whether or not pollution has an impact on the mortality rate. Taking data from 60 cities (n=60) where the responsive variable Y = mortality rate per population of 100,000, whose variables include Education, Percent of the population that is...

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