EBK THE ESSENTIALS OF STATISTICS: A TOO
EBK THE ESSENTIALS OF STATISTICS: A TOO
4th Edition
ISBN: 9780100557468
Author: HEALEY
Publisher: YUZU
bartleby

Concept explainers

Types of Bias
Statistics is the study of data collection, organization, analysis, interpretation, and presentation. Statistical bias is a characteristic of a statistical technique or its findings in which the expected value deviates from the actual root quantitative p…
bartleby

Videos

Textbook Question
Book Icon
Chapter 13, Problem 13.3P

Twelve families have been referred to a counselor, and she has rated each of them on a scale that measures family cohesiveness. Also, she has information on family income and number of children currently living at home. Take family cohesion as the dependent variable.

Family Cohesion Score Income Number of Children
A 10 30,000 5
B 10 70,000 4
C 9 35,000 4
D 5 25,000 0
E 1 55,000 3
F 7 40,000 0
G 2 60,000 2
H 5 30,000 3
I 8 50,000 5
J 3 25,000 4
K 2 45,000 3
L 4 50,000 0

a. Find the multiple regression equations (unstandardized).

b. What level of cohesion would be expected in a family with an income of $20,000 and six children?

c. Compute beta-weights for each independent variable and compare their relative effect on cohesion. Which was the more important factor?

d. Compute R 2 .

e. Write a paragraph summarizing your findings.

Expert Solution & Answer
Check Mark

Want to see the full answer?

Check out a sample textbook solution
Blurred answer
Previous
Chapter 13, Problem 13.2P
Students have asked these similar questions
Elementary StatisticsBase on the same given data uploaded in module 4, will you conclude that the number of bathroom of houses is a significant factor for house sellprice? I your answer is affirmative, you need to explain how the number of bathroom influences the house price, using a post hoc procedure. (Please treat number of bathrooms as a categorical variable in this analysis)Base on the same given data, conduct an analysis for the variable sellprice to see if sale price is influenced by living area. Summarize your finding including all regular steps (learned in this module) for your method. Also, will you conclude that larger house corresponding to higher price (justify)?Each question need to include a spss or sas output.       Instructions: You have to use SAS or SPSS to perform appropriate procedure: ANOVA or Regression based on the project data (provided in the module 4) and research question in the project file. Attach the computer output of all key steps (number) quoted in…
Elementary StatsBase on the given data uploaded in module 4, change the variable sale price into two categories: abovethe mean price or not; and change the living area into two categories: above the median living area ornot ( your two group should have close number of houses in each group). Using the resulting variables,will you conclude that larger house corresponding to higher price?Note: Need computer output, Ho and Ha, P and decision. If p is small, you need to explain what type ofdependency (association) we have using an appropriate pair of percentages.       Please include how to use the data in SPSS and interpretation of data.
An environmental research team is studying the daily rainfall (in millimeters) in a region over 100 days. The data is grouped into the following histogram bins: Rainfall Range (mm) Frequency 0-9.9 15 10 19.9 25 20-29.9 30 30-39.9 20 ||40-49.9 10 a) If a random day is selected, what is the probability that the rainfall was at least 20 mm but less than 40 mm? b) Estimate the mean daily rainfall, assuming the rainfall in each bin is uniformly distributed and the midpoint of each bin represents the average rainfall for that range. c) Construct the cumulative frequency distribution and determine the rainfall level below which 75% of the days fall. d) Calculate the estimated variance and standard deviation of the daily rainfall based on the histogram data.