Michael believes the following model is correct: Wage = B0 + B1 *Schooling + B2* Experience + B3*Experience2 + u Anna thinks the following model is correct: Wage = B0 + B2* Experience + B3* Experience2 + u 1) Cleo notes that you need a job to get a wage. Which one of the potential threats to internal validity does this relate to? 2) Peter notes that if you have a hi

Michael believes the following model is correct: Wage = B0 + B1 Schooling + B2 Experience + B3Experience2 + u Anna thinks the following model is correct: Wage = B0 + B2 Experience + B3* Experience2 + u 1) Cleo notes that you need a job to get a wage. Which one of the potential threats to internal validity does this relate to? 2) Peter notes that if you have a hi

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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A psychologist wants to test the influence of color on object recognition in 4-year olds. She recruits 25 children and shows them two sets of pictures of everyday objects (variable = picture type), has the children name them, and measures the time it takes (variable = reaction time). She shows the children a color set of pictures first and then shows them a black and white set of pictures. a) What is the independent variable? b) What is the dependent variable? c) What is the second independent variable? d) What is the second dependent variable? e) Is "picture type" a within-subjects or between-subjects variable? f) What scale of measurement is reaction time? g) What scale of measurement is picture type? h) The order of presentation of the picture sets is what kind of variable?
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5. In recent years there has been a great deal of research demonstrating gender discrimination in science, technology, engineering and math (STEM) fields. In one experiment, for example, faculty members viewed an application for a laboratory manager position. The applications were identical except that half had a traditionally male name (John) and half had a traditionally female name (Jennifer). In addition, half of the faculty participants were from STEM fields and half were from non-STEM fields. The faculty were asked to rate the competence of the applicants on a 6-point scale, with 1 indicating a lower rating. Group means are presented below, along with an incomplete summary table. After completing the table, write a conclusion about the outcome of the experiment. Source Gender of applicant Male Female Between Treatments Gender of applicant Discipline of rater A x B interaction Within treatments Total SS 320 80 576 Discipline of Faculty Rater STEM M = 4.80 M = 4.02 df MS 20 1.25…
The waiting times for customers to receive their food were recorded from two different fast-food branches (A & B). A B 20 21 22 26 19 17 23 18 16 21 24 17 21 19 20 22 18 22 15 19 The owner of these two branches wants to compare the waiting time between them. a) Write the research question.
Olivia attends school at the University of Alberta and decides to compile a contingency table of students who are taking various degrees. She surveys a group of students, and the data she collects is listed in the contingency table below. Olivia want to see if degree and gender are dependent variables. PhD Masters Undergraduate 22 74 62 ------+---+- Male 18 +---+ Female; 15: 25 -------- (a) In performing this statistical test, state the hypotheses. O Ho: The proportion of female students is the same as the proportion of male students vs. Ha: The proportion of female students is not the same as the proportion of male students O Ho: Degree is related to gender vs. Ha: Degree is not related to gender O Ho: Degree is associated with gender vs. Ha: Degree is not associated with gender O Ho: Degree and gender are dependent vs. Ha: Degree and gender are independent O Ho: Degree and gender are independent vs. Ha: Degree and gender are dependent (b) What is the expected frequencies of each…
A report from Texas Transportation Institute (Texas A&M University System, 2005) titled "Congestion Reduction Strategies" included the following data on extra travel time during rush hour for very large and for large urban areas. 2.27 Very Large Urban Areas Extra Hours per Year per Traveler Los Angeles, CA 93 San Francisco, CA 72 Washington DC-VA-MD 69 Atlanta. GA 67 Houston. TX 63 Dallas, Fort Worth, TX 60 Chicago, IL-IN 58 Detroit, MI 57 Miami, FL 51 Boston, MA-NH-RI 51 New York, NY-NJ-CT 49 Phoenix, AZ 49 Philadelphia, PA-NJ-DE-MD 38 Extra Hours per Year Large Urban Areas per Traveler Riverside, CA 55 Orlando, FL 55 San Jose, CA 53 San Diego, CA Denver, CO 52 51 Baltimore, MD 50 Seattle, WA 46 Tampa, FL Minneapolis, St Paul, MN Sacramento, CA Portland, OR-WA 46 43 40 39 Indianapolis, IN St Louis, MO-IL 38 35 San Antonio, TX 33 Providence, RI-MA 33 Las Vegas, NV Cincinnati, OH-KY-IN 30 30 Columbus, OH 29 Virginia Beach, VA Milwaukee, WI New Orleans, LA 26 23 18 Kansas City, MO-KS 17…
What is true about this use case diagram? daughter mother cook dinner «include>> mix cocktails Select one: Both daughter and mother cook dinner and the daughter only mixes cocktails O Both daughter and mother can even cook dinner or mix cocktails Both daughter and mother cook dinner and hence they will mix cocktails Both daughter and mother cook dinner and sometimes they mix cocktails
Suppose you are a basketball coach and you've taken some measures on your starting five players. The two measures that you're most interested in right now are scores on a two-minute jump shot test (x) and time in seconds on a shuttle run (y). You want to determine a couple of things:1) On which variable (jump shots or shuttle run time) are your starters more consistent? 2) For player #1, is she a faster runner or better at jump shots? 3) For player #4, is she a faster runner or better at jump shots? Player # Jump shot score (x) Shuttle run time (y) 1 17 37 2 20 45 3 4 59 4 34 48 5 22 42
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The Gendered Nature of Alternative Employment Arrangements Are the reasons for choosing alternative employment arrangements different for men and women? Reasons include family-related (childcare, other family/personal, and flexible schedule), work-related (to be own boss, money is better, and training) and other (only type of work could find, hope leads to permanent job, laid-off and rehired as contingent worker, health limitations, social security limitations, in school and other personal reasons). A two-way table summarizing the data is provided in the table below. Does the data provide enough evidence to show that there is an association between alternative employment arrangement and gender? Test at the 10% level and round expected values to one decimal place. Gender Male (Observed) Male (Expected Value) Female (Observed) Female (Expected Value) Row Total Family 538 420 958 Work 947 1155 2102 Other 526 527 1053 Column Total 2011 2102 4113 H:…