A student would like to know if the time spent on studying and number of lectures attended for an exam is related to the exam scores (marks). The student now collects data on the number of lectures attended in the same period. The information obtained is tabulated and the output from a multiple regression analysis is shown below: Regression Statistics Multiple R 0.859436 R Square 0.738631 Adjusted R Square 0.695069 Standard Error 9.963039 Observations 15 ANOVA SS MS F Significance F Regression 2 3366.187 1683.094 16.95605 0.000318805 Residual 12 1191.146 99.26216 Total 14 4557.333 Standard Upper Coefficients Error t Stat P-value Lower 95% 95% Intercept 24.10 15.34 1.571456 0.142058 -9.313897659 57.51084 Hours spent Studying 0.58 5.17 0.112479 0.912303 -10.68968118 11.85345 Number of lectures attended 5.24 4.45 1.179938 0.260888 -4.440035431 14.92977 Which of the following is the correct interpretation of the coefficient for the variable Number of lectures attended?Select one: 0 For every additional hour spent studying, the exam score is expected to increase on average by 0.58 marks. 0 For every additional lecture attended, the exam score is expected to increase on average by 5.24 marks. 0 Holding the number of lectures attended constant, for every hour spent studying, the exam score is expected to increase by 0.58 marks. 0 Holding the hour spent studying constant, for every number of lectures attended, the exam score is expected to increase by 5.24 marks. 0 Holding the number of lectures attended constant, for every additional hour spent studying, the exam score is expected to increase on average by 0.58 marks 0 Holding the hour spent studying constant, for every additional number of lectures attended, the exam score is expected to increase on average by 5.24 marks. Check