A manufactures of LED sets was trying to find out what variables influenced the purcnase of a LED set. Level of income was suggested as possible variable influencing the purchase of LED sets. A sample of 500 households was selected and the information obtained is classified as shown below : Have LED set Do not have LED set Low income group 0. 250 Middle income group 50 100 High income group 80 20 Is there evidence from the above data of a relation ownership of LED sets and level of income ?

Which set of data would probably show a strong positive linear correlation? a) the number of defective light bulbs produced and the time of the day when they were manufactured b) marks on a history test and the heights of the students c) the colour of cars sold and the annual income of the car buyers d) the height of corn in a field and the amount of precipitation during the growing season

8) The following results are from data that were collected from the various high schools around the county. The dependent variable is % OF STUDENTS GOING TO COLLEGE, and the independent variables are: AVERAGE CLASS SIZE, COMBINED SAT SCORES, SPENDING PER STUDENT, AVERAGE TEACHER SALARY, AND % TAKING THE SAT Since the 3 variables AVERAGE CLASS SIZE, SPENDING PER STUDENT, AND AVERAGE TEACHER SALARY are each not significant at the 10% level of significance individually, in order to test to see if as a group they are significant the 3 variables are excluded and another regression is run. The results are as follows: a) At the 10% level of significance, test whether as a group AVERAGE CLASS SIZE, SPENDING PER STUDENT, AND AVERAGE TEACHER SALARY are significant. Be sure to state the null and alternative hypotheses for this hypothesis test.

When analyzing an association between two variables, the size of the correlation may be deceptive because of a.) a spurious association b.) range restriction c.) conflated data d.) poor statistical validity

I want to assess the effects of diet (control diet, high-sugar diet, high-fat diet) and exercise (no voluntary running wheel, voluntary running wheel) on time spent in a target quadrant (more time indicates better memory). I record the percent time spent in a target quadrant for 30 mice and obtain the following data:    Control Diet High-sugar Diet High-fat diet No running wheel 15, 28, 29, 30, 25 24, 20, 30, 32, 20 19, 23, 22, 23, 25 Running wheel 30, 34, 35, 44, 32 21, 22, 28, 26, 29 30, 32, 28, 19, 26   What type of factorial design is this? (ex: # x #) ______________ What is the critical F value you’ll be making a decision based on (assume alpha = .05)?  Diet: ____ Exercise: _____ Interaction: ______

Is there a relation between incidents of child abuse and number of runaway children? A random sample of cities (over 10,000 population) gave the following information about the number of reported incidents of child abuse and the number of runaway children. (Reference: Federal Bureau of Investigation, U.S. Department of Justice.) City 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Abuse cases 113 33 41 60 52 99 31 56 15 67 106 59 45 74 84 Runaways 648 188 285 687 421 590 284 277 162 473 600 432 317 580 592 Use a 1% level of significance to test the claim that there is a monotone-increasing relationship between the ranks of incidents of abuse and number of runaway children. (a) Rank-order abuse using 1 as the largest data value. Also rank-order runaways using 1 as the largest data value. Then construct a table of ranks to be used for a Spearman rank correlation test. City Abuse CasesRank x RunawaysRank y d = x - y d2 123456789101112131415 Σd2 =  (b) What is the level of…

A. For which data set is the sample correlation coefficient r closest to −1? B. For which data set is the sample correlation coefficient r closest to 0? C. For which data set is the sample correlation coefficient r equal to 1?

A graphing calculator is recommended.The following table lists the number of pages in four different types of magazines. Home decorating News Health Computer 175 89 85 104 287 95 157 139 165 123 91 98 209 107 106 209 199 101 97 147 Using a significance level of 5%, test the hypothesis that the four magazine types have the same average length. (Let 1 = Home decorating, 2 = News, 3 = Health and 4 = Computer.) 1.)Enter an exact number as an integer, fraction, or decimal.df(num) =  2.) Enter an exact number as an integer, fraction, or decimal.df(denom) =  3.)What is the test statistic? (Round your answer to two decimal places.) 4.)What is the p-value? (Round your answer to four decimal places.) 5.)(i) Alpha (Enter an exact number as an integer, fraction, or decimal.)? =

The questions below are based on a dataset containing the characteristics of 5,407households. In particular, we will use the following variables:- size: home size, measured in square feet.- hhinc: annual household net income, measured in euros.- owner: dummy variable equal to 1 if the living space is owned, and 0 if the livingspace is rented.- hhsize1: dummy variable equal to 1 if the number of household’s members is 1 or2, and 0 otherwise.- hhsize2: dummy variable equal to 1 if the number of household’s members is 3 or4, and 0 otherwise.- hhsize3: dummy variable equal to 1 if the number of household’s members is 5 orabove 5, and 0 otherwise.- edu: education level of household’s members. We conduct a simple regression of size on hhinc, now using robust standard errors.The regression output is reported in Table 2. Why are the estimated coefficients inTable 2 equal to the estimated coefficients in Table 1? Do the conclusions on thestatistical significance at 5% of the coefficient of…