Prof. Murphy, always interested in improving her teaching effectiveness, has decided to undertake a careful analysis of her student evaluations from the past several years. The last question on the student evaluation form, Question17, is "Would you recommend this professor to another student?" A matter of special concern to Prof. Murphy is how she is viewed by students of different majors. Each of Prof. Murphy's students can be placed into a category according to the student's major school. (Students who have majors from more than one school are not included.) So, there are two variables under consideration: student's major school ("School of Social Sciences", "School of Engineering", or "School of Physical Sciences") and answer to Question17 ("No", "Maybe", or "Yes").The contingency table below contains a summary of the responses to Question 17 for a random sample of500 of Prof. Murphy's students. In each cell of the table is written three numbers: the first number is the observed cell frequency (fO); the second number is the expected cell frequency (fE) under the assumption that the variables student's major school and answer to Question 17 are unrelated; and the third number is the following value.Could not fit part 2 in the picture but the questions are asking for: type of test statisticvalue of test statistic p valueand can professor murphy conclude that the variable students major school and answer to question 17 are related? use the 0.05 level of significance. yes or no

Fill in the missing values in the contingency table. Round your expected frequencies to two or more decimal places, and round your Espanol values to SE three or more decimal places. Send data to Excel Student's major school X 5 ? School of School of Social School of Physical Total Sciences Engineering Sciences 53 32 11 "No" 25.54 96 1.634 44 20 34 Response to "Maybe" 26.07 98 Question 17 1.413 152 81 73 "Yes" 152.39 81.40 72.22 306 0.001 0.002 0.008 Total 249 133 118 500