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Problem Solving (2 points nch) The distribution of student ages in an elementary accounting dass is as givt'n in the table below. This table contains some missing values that you arc asked to supply In questions I through 3. Cumulative Relative Inter val Midpoint Frequency Frl'(1urncy Frequency 18-20 19 44 44 .594 21-23 22 ( .. ) 56 .162 24-{·) 25 8 64 .108 27-29 28 7 71 ( .. •) J0-32 JI 3 74 .041 I. What is the frequency for the i.ntervol 21-23, mo.riced ( ••) in the table? 2. What is the relative frequency oft he interval 27-29, marked c•••J in the 1able? Eleven contractors were coo1ac1cd 10 sec bow mnny new engineers they had hired during the last 2 ycnrs. 1'hc data are as follows: 3 () 6 8 0 5 7 0 2 3. Whnt is the mean of these data'? 4. What is the median of these data? A particular population of college men have weights distributed withμ = 80kg and u = 8kg. 5. l fit can be assumed that the population is normal, then what is the probability that one man sampled from this population bas a weight between 72kg and 88kg'? 6. l fit can be assumed that the population is normal, then what is the probability that the mean weight of four men sampled from this population lies between 72 and 88kg? 7. If it CANNOT be assumed that the population is normal then the probability that the mean weight of 64 men sampled from this population lies between 79 and 81 kg? A particular population of coUege men ba,•e weights distributed with 11 = 80kg and u = 8kg. 8. What is the probability that a randomly selected student has high stress 9. Given that a randomly selected student is from a Rural District, what is the probability that the student has high stress. I 0. In doing a Chi-Square test for independence. what is the Expected Value For the Students from a Rural District with High Stress. In order to assess the opinion of students at De Aoza CoUege, a reporter for the student newsp aper interviews the first six students he meets l\'ho are willing to express their opinion. 11. In the above case. what is the population? 12. In the abo,,e case. what is the sample'? The time for service call follows a uniform distribution over the interval 20 to 60 minutes. 13. What is the probability t hat the service call takes longer than 30 minutes 14. What is the interquartile range? 15. What is lbe 901h percentile? Complete the following ANOVA table for a one factor Analysis of Variance Model. ANOVA table Source Between Within Total ss 120 490 dJ MS 3 40 I 6. What is the Null hypothesis that corresponds to this test'] 17. What is the Mean Squared Within? F I 8. If 1he decision rule is 10 reject the null hypothesis if F>4.36. your decision would be: A basketball player makes 70°/4 of her free throws . 19. lfshe takes 20 free 1hrows. determine lhe expected number of made free throws. 20. If she takes 3 free 1hrows, determine lhe probability of at least one missed free throw. 21. X is lhe number of successes when she takes 10 free throws. What is Expected Value of X? 'nle reotessi.on equation 1.s Annual Pt•c1J> • • 169 + 5.32 Latieud.e: Predictot Coruste.nt Let.ltude COet -168,98 5,317 st Coet 41. 97 J.142 T - 4.0S 4,66 p 0,004 0.002 S • 11,0384 R-Sq • 73, I\ R-Sq(edi) • 69,7• Analy•ia ot Variance Soucee Re-11reaaion Rea1.d1.1a.l ! cror Toca! Dr SS l 2642. 6 8 974.8 9 3617. 3 11$ 2642. 6 121.8 r P 21.69 o.ooz ()Ma Md R"9dutll - S<- .. C,.tE_ Hf._.-Cil l .''. ",-, ·",-o ,, 11 41 ,., .. nfrMCIM 2111 -- ,,. 1411 ,,. UH - ,. . 141' JC) U..1..1.w..1..1.1..,.c .1,5 .0.1 ,. ' u, •-,o.!2!: ... ,., , A metrorologl~t was studying the relation ship hch.,·ccn annual preeipilation in inche.~ and northern latlludc for California coastal dties and those 10 use a regression model. Daht and Computer Output are shown above: 22. What is a possible null hypothesis for lhe ANO VA table shown above? 23. What is the coefficienl of detcnnina1ion (r1) '1 24. What is your decision if you use p_ value method to run the regression test? 25. Garbervillc is at la1irude 40.1 degrees nonh. Use 1hc regression equation to predict lhc annual rainfall for Garbcrvillc. ,,,,, ,,,n 1.,1,1e1~1 ,o ,,, .)0-fit ,n. o..,., •10 Ill 15111 1)9)4 , ou 11•11 , ... .,,,, 1 .. , 1.0.7..U. 1611 SO•~ 1. Use a x2 test to test the claim that in the given contingency table, the row variable and the column variable arc independent. (10 points) Responses to a survey question are broken down according to gender and the sample results are given below. At the 0.05 significance level. test !the claim that response and gender are independent. Yes No Undecided Male 25 50 15 female 20 30 10 2. Perform the indicated hypothesis test Asswme that the two s amples arc independent simple random samples select ed from normaU:y distributed populations. (10 points) A researcher was interested in comparing the amount of time spent watching television by women and by men. Independent simple random samples of 14 women and 17 men were selected, and each person was asked how many hours he or she had watched television during the previous week. The summary statistics are as follows. \'/omen Men x1 =1L4hr x2=l6.8hr s1 =4.l hr 52 = 4.7hr n1 = 14 Use a 0.05 significance level to test the claim that the mean amount of time spent watching television by women is smaller than the mean amount of time spent watching television by men. Use the traditional method of hypothesis testing. (Critical Value Method). Show all your work and graph.

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Problem 1
The total number of students is n = 74
Therefore, the frequency 88 is 74-(44+8+7+3)= 12
Problem 2
Divide the frequency by the total number of students
Relative Frequency = 7/74 = 0.0946
Problem 3
Mean = sum/(number of observations)
= 33/11
= 3
Problem 4
Median = middle value
= 6th lowest value
= 2...

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