3. Run a simple linear regression using EXCEL

1. Use Time period and Stock 1 prices. Show the output from Excel ( note the weeks must be changed to time periods 1,2,3...)
2. Set up the linear regression equation Stock 1
3. Test the significance using p-value with =0.05. Stock 1
4. Use Linear regression equation (from b) forecast the stock price for end of May 2022. Stock 1.
5. Draw Time-series plot for Stock 1
6. Do you notice any trends in e)? How would you adjust your forecast above in Q d)?

Stock 1 hypothesis testing: Hypothesised Population Mean () = 0.15 Sample Standard Deviation (s) = 4.997812556 Sample Size (n) = 60 Sample Mean (X) = 0.874635732 Significance Level (a) = 0.05 Stock 2 hypothesis testing: Hypothesised Population Mean () = 0.15 Sample Standard Deviation (s) = 6.530837047 Sample Size (n) = 60 Sample Mean (X) = -2.238574117 Significance Level (a) = 0.05Descriptive statistics Question 3 WRT (ILU.AX) WRT (BLD.AX) Mean 0.874635732 Mean -0.238574117 Standard Error 0.645214827 Standard Error 0.843127437 Median 1.243671007 Median 0.135501355 Mode #N/A Mode 0 Standard Deviation 4.997812556 Standard Deviation 6.530837047 Sample Variance 24.97813034 Sample Variance 42.65183253 Kurtosis 0.00598448 Kurtosis 23.12353498 Skewness -0.163788123 Skewness -3.534646635 Range 24.48791128 Range 54.7810215 Minimum -11.38996139 Minimum -39.81623277 Maximum 13.09794989 Maximum 14.96478873 Sum 52.47814392 Sum -14.31444704 Count 60 Count 60