(a) What forecasting model should be used for this data. Why? (5(b) Develop the forecasting model that you have proposed in (a). (c) Compute the relationship for these data. In your opinion, is the relationship between independent variable strong enough to base a predictive the dependent variable? Explain your answer.
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.
An electronic appliance manufacturer wants to know if there is a relationship between percentage change in deposable personal income which is reported quarterly by the government, and the percentage change in appliances sold by the manufacturer following same years of quarterly data. Brenda Chee and Clarence Paulus lead an analyst team has obtained data for the past 10 quarters. (Hint: Provides your answers in two decimal points)
|
Quarter |
Percent change in income |
Percent Change in appliance sold |
Quarter |
Percent change in income |
Percent change in appliance sold |
|
1 |
-2.3 |
-2.5 |
6 |
-1.0 |
1.0 |
|
2 |
-1.5 |
-1.0 |
7 |
0.7 |
1.4 |
|
3 |
2.8 |
7.4 |
8 |
5.2 |
3.4 |
|
4 |
0.5 |
2.6 |
9 |
-2.5 |
-0.5 |
|
5 |
4.6 |
8.5 |
10 |
1.7 |
1.8 |
(a) What forecasting model should be used for this data. Why?
(5(b) Develop the forecasting model that you have proposed in (a).
(c) Compute the relationship for these data. In your opinion, is the relationship between independent
variable strong enough to base a predictive the dependent variable? Explain your answer.
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