A time series regression equation measuring the number of surfboards sold by a surfboard manufacturing company in Australia is given below: Y = 35 + 4Q1+0.5Q3 + 8Q4 + 3t with t in quarters and the first observation of the dataset is December 2015 and Q1 is the indicator variable for March, Q3 is the indicator variable for September and Q4 is the indicator variable for December. Which of the following statements is correct? There is a mistake with this regression model because all the coefficients of the indicator variables are positive. There is no indicator variable for the June quarter in this model because there is no seasonal effect in June due to winter in Australia. There is a mistake with this model because the indicator variable for the June quarter has been left out. There is no indicator variable for the June quarter because the model has an intercept and including the June quarter would result in perfect multicollinearity.

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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.