YEAR Sales(Millions Euro) Advertising(Million Euro) 1 651 23 2 762 26 3 856 30 4 1063 34 5 1190 43 6 1298 48 7 1421 52 8 1440 57 9 1518 58 a) Calculate the Pearson Product moment correlation coefficient for this set of data. b) Fit a simple linear regression model for the following data taking sales (million euro) as predictand variable. c) Interpret what does regression coefficient indicates in the above model.

Determine if correlation between the two given variables is likely to be positive or negative, or if they are not likely to display a linear relationship.  Your daily calorie intake and weight. (a) Positive (b) Negative (c) No correlation

Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $105 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 41 23 114 75 78 47 120 64 10 59 127 22 12 150 2 0 127 18 111 65 113 112 102 94 64 98 211 41 22 288 57 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... x. (Round to one decimal place as needed.) The regression equation is = + The best predicted gross for a movie with a $105 million budget is $ million. (Round to one decimal place as needed.)

There is a dataset of size n = 51 and is for the 50 states and the District of Columbia in the United States. The dependent variable is year 2002 birth rate per 1000 females 18 to 19 years old and independent variable is the violent crime rate (per 1000 population). A simple linear regression model is run with the results given below. What is the Pearson correlation coefficient between x and y variables? The R squared of the model? What kind of relationship there is?