Concept explainers
Videos
a.
Identify the dependent variable and independent variable.
a.
Answer to Problem 1SR
The dependent variable is the ‘sales revenue’ and the independent variable is the ‘advertising expense’.
Explanation of Solution
Data on the number of times the advertisement was aired and digital camera sales are given.
Independent variable:
The variable that can be used to predict the values of other variable is called an independent variable.
Dependent variable:
The variable that can be predicted by other variables is called a response variable or a dependent variable.
Here, the variable ‘sales revenue’ can be predicted using the variable ‘advertising expense’. Therefore, the dependent variable is the ‘sales revenue’ and the independent variable is the ‘advertising expense’.
b.
Construct a
b.
Answer to Problem 1SR
The scatter diagram of the data is represented below:
Explanation of Solution
Calculation:
The scatterplot of the data is as follows:
Software Procedure:
Step-by-step procedure to obtain the scatterplot using Mega Stat software:
- In an EXCEL sheet enter the data values of x and y.
- Go to Add-Ins > Mega Stat >
Correlation/Regression > Scatterplot. - Enter horizontal axis as $A$1:$A$5 and vertical axis as $B$1:$B$5.
- Click on OK.
The scatterplot of the data shows an increasing trend.
c.
Find the
c.
Answer to Problem 1SR
Thus, the
Explanation of Solution
Calculation:
Software procedure:
Step-by-step procedure to obtain the correlation matrix using Mega Stat software:
- In an EXCEL sheet enter the data values of x and y.
- Go to Add-Ins > Mega Stat > Correlation/Regression > Correlation matrix.
- Enter Input
Range as $A$1:$b$5. - Click on OK.
Output obtained using Mega Stat is given as follows:
Thus, the correlation coefficient is 0.965.
d.
Interpret the strength of the correlation coefficient.
d.
Explanation of Solution
From Part (c), the correlation coefficient is 0.965. Since the correlation coefficient is positive and close to 1, there is a strong
Want to see more full solutions like this?
Chapter 13 Solutions
STATISTICAL TECH IN BUSN CONNECT <LCPO>
- (c) Utilize Fubini's Theorem to demonstrate that E(X)= = (1- F(x))dx.arrow_forward(c) Describe the positive and negative parts of a random variable. How is the integral defined for a general random variable using these components?arrow_forward26. (a) Provide an example where X, X but E(X,) does not converge to E(X).arrow_forward
- (b) Demonstrate that if X and Y are independent, then it follows that E(XY) E(X)E(Y);arrow_forward(d) Under what conditions do we say that a random variable X is integrable, specifically when (i) X is a non-negative random variable and (ii) when X is a general random variable?arrow_forward29. State the Borel-Cantelli Lemmas without proof. What is the primary distinction between Lemma 1 and Lemma 2?arrow_forward
