In a two-way ANOVA, the main effect of a factor is the...

An industrial psychologist feels that a big factor in job turnover among assembly-line workers is the individual employees' self-esteem. He thinks that workers who change jobs often (population A) have, on the average, lower self-esteem, as measured by standardized test, than workers who do not (population B). To determine whether he can support his belief with statistical analysis, he draws a simple random sample of employees from each population and gives a test measuring self-esteem. The results are as follows. At 0.05 level of significance and assuming equal variances. Mean Standard Deviation Sample size A 52.3 9.23 10 69.47 11.78 17 Provide the tabular and computed value of the test statistic. O a. 1.703; 3.05 O b. 2.06; 3.94 O . 1.708; 4.01 O d. 2.052; 3.46

W. Thomas Boyce, a professor and pediatrician at the University of British Columbia, Vancouver, has studied interactions between individual differences in physiology and differences in experience in determining health and well-being. Dr. Boyce found that some children are more sensitive to their environments. They do exceptionally well when the environment is supportive but are much more likely to have mental and physical health problems when the environment has challenges. You decide to do a similar study, conducting a factorial experiment to test the effectiveness of one environmental factor and one physiological factor on a physical health outcome. As the environmental factor, you choose two levels of stressful life events. As the physiological factor, you choose three levels of immune reactivity. The outcome is number of respiratory illnesses in the previous 12 months, and the research participants are kindergartners.

For a two-factor ANOVA with two levels of factor A, two levels of factor B, and a separate sample of n = 8 participants in each treatment condition, the two means for level A1 are 3 and 5, and the two means for level A2 are 4 and 2. For these data, what is the value of SSbetween treatments?

Most Australian youth-sports leagues separate athletes by birthdate, and the cutoff date is January 1st. Thus, those children born in January and February have some physical advantages in youth sports over those born in November and December. A recent studysuggests that those physical advantages enjoyed early in life impact the likelihood of a child becoming a professional athlete. The table gives the number of Australian-born 2009 Australian Football League players born in different months of the year, as well as the proportion of births expected if the birthdates of the athletes matched the distribution of all births nationally. Is there evidence that the distribution of birthdates of AFL athletes is not the same as the distribution of birthdates nationally?   Birthdates nationally in Australia and for Australian football players   Proportion Actual for Months Nationally AFL players Jan-Mar 0.248 196 Apr-June 0.251 162 Jul-Sep 0.254 137…

What would be the percentage of this question?

A factor in determining the usefulness of an examination as a measure of demonstrated ability is the amount of spread that occurs in the grades. If the spread or variation of examination scores is very small, it usually means that the examination was either too hard or too easy. However, if the variance of scores is moderately large, then there is a definite difference in scores between "better," "average," and "poorer" students. A group of attorneys in a Midwest state has been given the task of making up this year's bar examination for the state. The examination has 500 total possible points, and from the history of past examinations, it is known that a standard deviation of around 60 points is desirable. Of course, too large or too small a standard deviation is not good. The attorneys want to test their examination to see how good it is. A preliminary version of the examination (with slight modifications to protect the integrity of the real examination) is given to a random sample of…

A sociologist studying New York City ethnic groups wants to determine if there is a difference in income for immigrants from four different countries during their first year in the city. She obtained the data in the following table from a random sample of immigrants from these countries (incomes in thousands of dollars). Use a 0.05 level of significance to test the claim that there is no difference in the earnings of immigrants from the four different countries. Country I Country II Country III Country IV 12.3 8.3 20.4 17.3 9.1 17.2 16.5 8.7 10.9 19.2 22.8 14.2 8.8 10.2 5.5 21.4 16.1   19.2 19.3   (b) Find SSTOT, SSBET, and SSW and check that SSTOT = SSBET + SSW. (Round your answers to three decimal places.) SSTOT =   SSBET =   SSW =   Find d.f.BET, d.f.W, MSBET, and MSW. (Round your answer to three decimal places for MSBET and MSW.) dfBET =   dfW =   MSBET =   MSW =   Find the value of the sample F statistic. (Round your answer to three decimal…

A sociologist studying New York City ethnic groups wants to determine if there is a difference in income for immigrants from four different countries during their first year in the city. She obtained the data in the following table from a random sample of immigrants from these countries (incomes in thousands of dollars). Use a 0.05 level of significance to test the claim that there is no difference in the earnings of immigrants from the four different countries. Country I Country II Country III Country IV 12.9 8.8 20.6 17.7 9.8 17.9 16.8 8.7 10.7 19.8 22.6 14.1 8.5 10.3 5.8 21.7 16.9   19.3 19.5 (b) Find SSTOT, SSBET, and SSW and check that SSTOT = SSBET + SSW. (Round your answers to three decimal places.) SSTOT =   SSBET =   SSW =   Find d.f.BET, d.f.W, MSBET, and MSW. (Round your answer to three decimal places for MSBET and MSW.) dfBET =   dfW =   MSBET =   MSW =   Find the value of the sample F statistic. (Round your answer to three decimal…

A manufacturer of laptop computers claims that only 1% of their computers are defective. In a sample of 600 computers, it was found that 3% were defective. If the proportion of defectives were really only 1%, there would be than 1 chance in 1000 of getting such a large proportion of defective laptops in the sample. Is there statistically significant  evidence against the manufacturer's claim? Why or Why not?