C. To test the null hypothesis that computer programmers' college major is not related to their programming capabilities, the work of 100 randomly chosen programmers was rated as either weak or strong. The following crosstabulation was obtained: Programming Capability Major WeakStrong Humanities:1212 Science:1224 Business:2416 1.If the null hypothesis is correct, how many Business majors with weak programming capability would we expect to find in our sample? (That is, what is the expected frequency for that cell?) 2.The computed value of χ2 (chi-square) for this table is 5.45. Should the null hypothesis be rejected at the .05 level of significance? (Be sure to show the statistics that lead to your decision.) 3.Treating college major as the independent variable, calculate and interpret an appropriate measure of association. 4.Using and reporting the appropriate percentages, show which major has the strongest programming capability. D. Suppose you are interested in the relationship between educational attainment (measured by years of completed schooling) and the how long people live (measured by age at death in years). For a sample of 100 recently-deceased people, you collect information on their educational attainment and their age at death. Treating educational attainment as the independent variable (X) and age at death as the dependent variable (Y), you compute the following regression equation. Y = 55 + 2.0X + e 1.Interpret in words this equation. That is, what do each of the numerical values in the equation tell us? Be specific. 2.How long would you predict that someone with a college education (that is, someone with 16 years of schooling) will live? E. A researcher wants to know if there is a relationship between year in college (X) (1=freshman, 2=sophomore, 3=junior, 4=senior) and percent of class lectures attended (Y). For a sample of 10 students, the following results are obtained: ΣX = 23 ΣY = 730 ΣXY = 1630 ΣX2 = 65 ΣY2 = 54100 X̅ = 2.3 Y̅ = 73 Σ(Y-Y̅)2 = 810 Σ(Ŷ-Y̅)2 = 198.3 Σ(Y-Ŷ)2 = 611.7 1.Compute the correlation coefficient between year in college and percent of class lectures attended. What does this value tell us? 2.Using a significance level of .05, test the null hypothesis that, in the population, the correlation between year in college and percent of class lectures attended is zero. E. (continued) 3.Compute and interpret the coefficient of determination (R2). F. Whenever we look at the relationship between two variables (regardless of the level of measurement of those variables), we are interested in two aspects of that relationship. What are those two "aspects" and why is each important? (You can discuss more than two if you feel it necessary).

C. To test the null hypothesis that computer programmers' college major is not related to their programming capabilities, the work of 100 randomly chosen programmers was rated as either weak or strong. The following crosstabulation was obtained: Programming Capability Major WeakStrong Humanities:1212 Science:1224 Business:2416 1.If the null hypothesis is correct, how many Business majors with weak programming capability would we expect to find in our sample? (That is, what is the expected frequency for that cell?) 2.The computed value of χ2 (chi-square) for this table is 5.45. Should the null hypothesis be rejected at the .05 level of significance? (Be sure to show the statistics that lead to your decision.) 3.Treating college major as the independent variable, calculate and interpret an appropriate measure of association. 4.Using and reporting the appropriate percentages, show which major has the strongest programming capability. D. Suppose you are interested in the relationship between educational attainment (measured by years of completed schooling) and the how long people live (measured by age at death in years). For a sample of 100 recently-deceased people, you collect information on their educational attainment and their age at death. Treating educational attainment as the independent variable (X) and age at death as the dependent variable (Y), you compute the following regression equation. Y = 55 + 2.0X + e 1.Interpret in words this equation. That is, what do each of the numerical values in the equation tell us? Be specific. 2.How long would you predict that someone with a college education (that is, someone with 16 years of schooling) will live? E. A researcher wants to know if there is a relationship between year in college (X) (1=freshman, 2=sophomore, 3=junior, 4=senior) and percent of class lectures attended (Y). For a sample of 10 students, the following results are obtained: ΣX = 23 ΣY = 730 ΣXY = 1630 ΣX2 = 65 ΣY2 = 54100 X̅ = 2.3 Y̅ = 73 Σ(Y-Y̅)2 = 810 Σ(Ŷ-Y̅)2 = 198.3 Σ(Y-Ŷ)2 = 611.7 1.Compute the correlation coefficient between year in college and percent of class lectures attended. What does this value tell us? 2.Using a significance level of .05, test the null hypothesis that, in the population, the correlation between year in college and percent of class lectures attended is zero. E. (continued) 3.Compute and interpret the coefficient of determination (R2). F. Whenever we look at the relationship between two variables (regardless of the level of measurement of those variables), we are interested in two aspects of that relationship. What are those two "aspects" and why is each important? (You can discuss more than two if you feel it necessary).

Social Psychology (10th Edition)

10th Edition

ISBN:9780134641287

Author:Elliot Aronson, Timothy D. Wilson, Robin M. Akert, Samuel R. Sommers

Publisher:Elliot Aronson, Timothy D. Wilson, Robin M. Akert, Samuel R. Sommers

Chapter1: Introducing Social Psychology

Section: Chapter Questions

Problem 1RQ1

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Related questions

Question

Programming Capability

Major WeakStrong

Humanities:1212

Science:1224

Business:2416

1.If the null hypothesis is correct, how many Business majors with weak programming capability would we expect to find in our sample? (That is, what is the expected frequency for that cell?)

2.The computed value of χ2 (chi-square) for this table is 5.45. Should the null hypothesis be rejected at the .05 level of significance? (Be sure to show the statistics that lead to your decision.)

3.Treating college major as the independent variable, calculate and interpret an appropriate measure of association.

4.Using and reporting the appropriate percentages, show which major has the strongest programming capability.

D. Suppose you are interested in the relationship between educational attainment (measured by years of completed schooling) and the how long people live (measured by age at death in years). For a sample of 100 recently-deceased people, you collect information on their educational attainment and their age at death. Treating educational attainment as the independent variable (X) and age at death as the dependent variable (Y), you compute the following regression equation.

Y = 55 + 2.0X + e

1.Interpret in words this equation. That is, what do each of the numerical values in the equation tell us? Be specific.

2.How long would you predict that someone with a college education (that is, someone with 16 years of schooling) will live?

E. A researcher wants to know if there is a relationship between year in college (X) (1=freshman, 2=sophomore, 3=junior, 4=senior) and percent of class lectures attended (Y). For a sample of 10 students, the following results are obtained:

ΣX = 23

ΣY = 730

ΣXY = 1630

ΣX2 = 65

ΣY2 = 54100

X̅ = 2.3

Y̅ = 73

Σ(Y-Y̅)2 = 810

Σ(Ŷ-Y̅)2 = 198.3

Σ(Y-Ŷ)2 = 611.7

1.Compute the correlation coefficient between year in college and percent of class lectures attended. What does this value tell us?

2.Using a significance level of .05, test the null hypothesis that, in the population, the correlation between year in college and percent of class lectures attended is zero.

E. (continued)

3.Compute and interpret the coefficient of determination (R2).

F. Whenever we look at the relationship between two variables (regardless of the level of measurement of those variables), we are interested in two aspects of that relationship. What are those two "aspects" and why is each important? (You can discuss more than two if you feel it necessary).

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