Solve a regression problem using SPSS - Coursework Example

The Equation of Best Fit is a calculation or equation that attempts to minimize distance between all the data points and a fitted line. The general idea is that small and unbiased difference between a model’s predicted values and the observed values indicates the model of best fit. However, it is advisable to look at the residual plots before concluding about goodness-of-fit as a statistical measure. We interpret the slope b or regression coefficient as the amount of change in Y for each unit increase in X.

that is b represents the effect of X on Y while the intercept a, is the predicted value of Y associated with X = 0. From our analysis, the slope (a = 0.124) and Y-intercept (-1.031), X-temperature, and Y ice cream sales. Figure 2 below shows the strong positive correlation between temperature and Ice Cream Sales (slope). The main idea for this task is to find out whether the number of ice cream sold varies with temperature. Based on existing literature, we would expect ice-cream sales to increase with temperature.

In order to answer the questions for the exercise, the Number of Ice Cream Sales is the dependent variable (criterion variable), and Temperature is the independent variable. Overall, the task is a simple linier regression because there are only two variables. Figure 4 above shows the correlation coefficient (r) is +0.98, which tells us a strong positive correlation between sales of ice cream and temperature, at 0.001 significance level. Therefore, we establish that the relationship between sales of ice cream and temperature was positively and strongly related (r = +0.98), p