Accountants at the Tucsan firm Larry Youdleman cpas believed that several traveling executives were submitting unusually high travel vouchers wehn they returned from business trips. First they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple regression equation relating expected travel cost to number of days on the road (X1) and distance traveled (X2) in miles ^y= $95.00+$50.50X1+$0.40X2 The coefficient of correlation for the model is 0.72 a) If Donna Battista returns from a 300 mile trip that took her out of tow for 6 days the expected amount that she should claim as expense = $518 b) after the 300 mile and 6 day trip Battista submitted a reimbursement request dfor $785 which is different than predicted value. The accountant should question the voucher as the request is much higher than expected
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.
Accountants at the Tucsan firm Larry Youdleman cpas believed that several traveling executives were submitting unusually high travel vouchers wehn they returned from business trips. First they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple regression equation relating expected travel cost to number of days on the road (X1) and distance traveled (X2) in miles
^y= $95.00+$50.50X1+$0.40X2
The coefficient of
a) If Donna Battista returns from a 300 mile trip that took her out of tow for 6 days the expected amount that she should claim as expense = $518
b) after the 300 mile and 6 day trip Battista submitted a reimbursement request dfor $785 which is different than predicted value. The accountant should question the voucher as the request is much higher than expected
c) Additional variables that could be included in the model are (select that choice that has all the factors you would consider)
Type of travel
The percentage of variation in the trip cost that can be explained by the model= [__]% (round your response to two decimal places) which suggests that the model is [particularly a good one/ Not particularly a good one]?
Here we will find the Expected tr avel cost
Expected travel cost =
In this part , we have , X1=Number of Days =6
X2=Travelled distance( in miles) =300
Hence, total expected travel cost =
Hence, The Expected amount that she should claim as expense =
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