R Square0.996423791Adjusted R Square0.99606617Standard Error47.0629563Observations12ANOVAdfMSFRegression16171342.448 6171342 2786.257Residual1022149.21856 2214.922Total116193491.667CoefficientsStandard Errort StatP-valueIntercept783.778218868.34114772 11.46861 4.47E-07Hours6.7771024560.12839066 52.78501 1.44E-13A key statistic that indicates reliability of the regression is:Multiple Choice783.338.O 6.777.12.09964 Burmer Co. has accumulated data to use in preparing its annual profit plan for the upcoming year.The cost behavior pattern of the maintenance costs must be determined. Data regarding themachine hours and maintenance costs for the last year and the results of the regression analysisare as follows:Maintenance MachineMonthCostHoursJan.$ 5,040620Feb.3,600420Mar.4,320520Apr.3,380390Мay5,220650June3,550400July3,6405,360430Aug.680Sept.5,110640Oct.4,860610Nov.3,960460Dec.3,790440Sum$51,8306,260Average$ 4,319522A staff assistant has run regression analyses on the data and obtained the following output usingExcel:REGRESSION ANALYSISY (Dependent) Variable: Maintenance CostX (Independent) Variable: Maintenance Hours

The coefficient of determinationR2 is the reliability of the regression. Thus, the key statistic…

Answered: A key statistic that indicates…

Math

Statistics

A key statistic that indicates reliability of the regression is: Multiple Choice 783.338. 6.777. 12 0 9964

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

Problem 31EQ

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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

R Square
0.996423791
Adjusted R Square
0.99606617
Standard Error
47.0629563
Observations
12
ANOVA
df
MS
F
Regression
1
6171342.448 6171342 2786.257
Residual
10
22149.21856 2214.922
Total
11
6193491.667
Coefficients
Standard Error
t Stat
P-value
Intercept
783.7782188
68.34114772 11.46861 4.47E-07
Hours
6.777102456
0.12839066 52.78501 1.44E-13
A key statistic that indicates reliability of the regression is:
Multiple Choice
783.338.
O 6.777.
12.
09964

Burmer Co. has accumulated data to use in preparing its annual profit plan for the upcoming year.
The cost behavior pattern of the maintenance costs must be determined. Data regarding the
machine hours and maintenance costs for the last year and the results of the regression analysis
are as follows:
Maintenance Machine
Month
Cost
Hours
Jan.
$ 5,040
620
Feb.
3,600
420
Mar.
4,320
520
Apr.
3,380
390
Мay
5,220
650
June
3,550
400
July
3,640
5,360
430
Aug.
680
Sept.
5,110
640
Oct.
4,860
610
Nov.
3,960
460
Dec.
3,790
440
Sum
$51,830
6,260
Average
$ 4,319
522
A staff assistant has run regression analyses on the data and obtained the following output using
Excel:
REGRESSION ANALYSIS
Y (Dependent) Variable: Maintenance Cost
X (Independent) Variable: Maintenance Hours

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Midgett Co. has accumulated data to use in preparing its annual profit plan for the upcoming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff suggested that linear regression be employed to derive an equation for maintenance hours and costs. Data regarding the maintenance hours and costs for the last year and the results of the regression analysis are as follows: Month MaintenanceCost Machine Hours Jan. $ 5,040 620 Feb. 3,648 420 Mar. 4,320 520 Apr. 3,331 390 May 5,221 650 June 3,550 400 July 3,655 430 Aug. 5,365 690 Sept. 5,110 640 Oct. 4,866 610 Nov. 3,944 460 Dec. 3,790 440 Sum $ 51,840 6,270 Average $ 4,320.00 522.50 Average cost per hour ($51,840/6,270) = $8.27 (rounded to the nearest cent)r = 0.99821r2 = 0.99780The percent of the total variance that can be…
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