Beachcomber Ltd in a local car dealership that sells used and new vehicles. The manager of the company wants to know how different variables affect the sales of his vehicles. A random sample of yearly data was taken with the view to testing the model: SALĖS=a+BAGE+YMIL+8ENG Where SALES= amount that a vehicle is sold for($000's), AGE = age of the vehicle, MIL= the total mileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data was processed using MINITAB and the following is an extract of the output obtained: The regression equation is ***** Coef StDev t-ratio p-value Predict or Constan 1.7586 0.2525 6.9648 0.0000 t AGE 0.2124 0.3175 0.5042 MIL -0.7527 0.3586 -2.0991
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.
Using statistical tables, show all workings.
What is dependent and independent variables? Also Fully Write out the regression equation.
Fill in the missing values ‘*’, ‘**’, ‘***’and ‘****’
Hence test whether ? is significant. Give reasons for your answer
![Beachcomber Ltd in a local car dealership that sells used and new vehicles. The manager of the
company wants to know how different variables affect the sales of his vehicles. A random sample of
yearly data was taken with the view to testing the model:
SALES=a+BAGE+YMIL+8ENG
Where SALES= amount that a vehicle is sold for($000's), AGE = age of the vehicle, MIL= the total
mileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data was
processed using MINITAB and the following is an extract of the output obtained:
The regression equation is *****
Coef
StDev
t-ratio
p-value
Predict
or
Constan
1.7586
0.2525
6.9648
0.0000
t
AGE
0.2124
0.3175
0.5042
MIL
-0.7527
0.3586
-2.0991
**
ENG
4.8124
***
7.7664
0.0000
Analysis of Variance
Source
DF
MS
Regressi
3
413.1291
138.709
****
0.00
on
7
Error
50
457.7607
2.2888
Total
53](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb7295e88-6129-40b3-8633-b93adcd7c23b%2F31b76b62-4d85-4007-991c-60d4558a765d%2Fexoenp_processed.png&w=3840&q=75)
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