Applied Social Statistics
Final Exam
Course Introduction
Applied Social Statistics introduces students to the practical use of statistical methods in the analysis of social science data. The course covers techniques such as data collection, data coding, descriptive statistics, inferential statistics, hypothesis testing, correlation, regression analysis, and non-parametric methods, with a focus on interpreting real-world social phenomena. Emphasizing hands-on experience, students will learn to utilize statistical software to manage and analyze datasets, gaining skills essential for conducting empirical research in sociology, political science, psychology, and related fields. The course bridges theoretical concepts and practical application, enabling students to critically evaluate statistical findings and apply quantitative reasoning to complex social issues.
Recommended Textbook
Social Statistics for a Diverse Society 8th Edition by Chava Frankfort Nachmias
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12 Chapters
614 Verified Questions
614 Flashcards
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Page 2
Chapter 1: The What and the Why of Statistics
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Sample Questions
Q1) The total set of cases,objects,groups,or events in which the researcher is interested is called the A)population.
B)sample.
C)entity.
D)variable.
Answer: A
Q2) The total set of individuals,objects,groups,or events in which the researcher is interested is defined as A)data. B)sample. C)variable.
D)population. Answer: D
Q3) A subset of cases selected from the total set of cases is referred to as the A)population. B)sample. C)entity.
D)variable. Answer: B
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Chapter 2: The Organization and Graphic Presentation of Data
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Sample Questions
Q1) Which graphic device would be most appropriate to display information about the following statement? "Undocumented migration from Mexico to the United States has increased each decade from the end of the Bracero Accord in 1964 through 2005."
Answer: A time-series chart
Q2) A relative frequency obtained by dividing the frequency in each category by the total number of cases and multiplying by 100 is a A)count.
B)frequency.
C)proportion.
D)percentage.
Answer: D
Q3) A rate is usually expressed as a A)count.
B)frequency.
C)multiple of the sample size.
D)multiple of some power of 10.
Answer: D
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Page 4
Chapter 3: Measures of Central Tendency
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Sample Questions
Q1) Consider the following distribution: 5,5,8,9,10,10,11.Which of the following is a correct statement about this distribution?
A)The mode is 9.
B)The median is 7.
C)The distribution is bimodal.
D)The mean is 6.5
Answer: C
Q2) Which of the following statements are not true?
A)If we add the mean from each score and multiply up all the sums,the product will always be one.
B)If we add the mean from each score and add up all the sums,the sum will always be zero.
C)If we subtract the mean from each score and add up all the differences,the sum will always be zero.
D)If we subtract the mean from each score and multiply up all the differences,the product will always be one.
Answer: A,B,D
Q3) Which is more susceptible to extreme values: the mean or the median?
Answer: The mean is more susceptible to extreme values.
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Page 5
Chapter 4: Measures of Variability
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Sample Questions
Q1) Calculate the value of the interquartile range for the following sub-sample: 24,27,35,31,21,22,28,18,25,24,36,20.
Q2) Which measure of variability is used for interval-ratio variables and is the square root of the average of the squared deviations from the mean?
A)IQV
B)Interquartile range
C)Variance
D)Standard deviation
Q3) Calculate the value of the interquartile range for the following sub-sample: 2,7,4,4,1,2,2,3,1,2,4,5.
Q4) The range is based on only one score.
A)True
B)False
Q5) The formula for calculating interquartile range is
A)Q3 - Q1.
B)Q1 - Q3.
C)25th percentile - 75th percentile.
D)75th percentile - 25th percentile.
Q6) What is the most basic consideration in choosing a measure of variability?
Page 6
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Chapter 5: The Normal Distribution
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Sample Questions
Q1) A normal distribution represented in standard Z scores,with
A)mean = 0 and standard deviation = 1.
B)mean = 1 and standard deviation = 0.
C)mean = 0 and standard deviation = 0.
D)mean = 1 and standard deviation = 1.
Q2) The annual salaries of employees in a large company are normally distributed with a mean of $50,000 and a standard deviation of $20,000.What percent of people earn between $45,000 and $65,000?
Q3) The mean age at first marriage for respondents in a survey is 23.33,with a standard deviation of 6.13.The Z score associated with a particular age at first marriage is 0.35.If the proportion of the area between this particular age at first marriage and the mean is 0.14,what proportion of respondents experienced their first marriage earlier than this age?
Q4) The mean number of siblings for respondents in a survey is 3.76 with a standard deviation of 3.18.Calculate the Z score associated with three siblings and provide a substantive interpretation of this quantity.
Q5) Scores for an exam are normally distributed with a mean of 235 and a standard deviation of 52.What is the percentile rank of a raw score 287?
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Chapter 6: Sampling and Sampling Distributions
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Sample Questions
Q1) The sampling distribution is less skewed.It resembles a normal distribution.
A)True
B)False
Q2) In a population of 250 students,60% are Whites,20% are Latinos,15% are Blacks,and 5% others.In a proportionate stratified random sample of 120, A)the number of Whites selected is 72.
B)the number of Blacks selected is 50.
C)the number of Latinos selected is 37.
D)the number of other racial and ethnicity background selected is 6.
Q3) The Law School Admission Test (LSAT)is designed so that test scores are normally distributed.The mean LSAT score for the population of all test-takers in 2005 was 154.35 with a standard deviation of 5.62.From Data Set 1,provide evidence that the standard error of the mean decreases as sample size increases.
Q4) Define systematic random sampling approach.
Q5) Which of the following is the notation for the population mean?
Q6) What is the major drawback of using the proportionate stratified sample?
Page 8
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Chapter 7: Estimation
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Sample Questions
Q1) Provide a hypothetical numerical example which demonstrates that the precision of a confidence interval is in part a function of sample size.
Q2) Because population parameters are typically unknown,we use the ______ to estimate the value of the standard error.
A)sample standard deviation
B)population standard deviation
C)sample proportion
D)population proportion
Q3) If the sample size goes up,the confidence level becomes less precise.
A)True
B)False
Q4) In a survey sample of 83 respondents,about 30.1 percent of the sample work less than 40 hours per week.What is the estimated standard error of the proportion for this group?
Q5) In a survey sample of 83 respondents,the mean number of hours worked per week is 39.04,with a standard deviation of 11.51.The sample size is 83.Estimate the value of the standard error.
Q6) Briefly describe how you would establish a confidence interval for a mean or proportion.
Page 9
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Chapter 8: Testing Hypotheses
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Sample Questions
Q1) The probability at which the null hypothesis is rejected is referred to as A)alpha.
B)beta.
C)Z score.
D)p value.
Q2) The t distribution is also bell-shaped like the standard normal distribution.
A)True
B)False
Q3) The probability associated with rejecting the null hypothesis when it is true is called A)Type I error.
B)Type II error.
C)alpha.
D)lambda.
Q4) To calculate the t statistic,we need to know the values of A)sample mean.
B)population mean.
C)sample standard deviation.
D)sample size.
Q5) Define Type I and Type II error.
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Chapter 9: Bivariate Tables
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Sample Questions
Q1) Once the appropriate percentages for a bivariate table are calculated,one then examines the ______ of these quantities across the categories of the independent variable.
A)sum
B)difference
C)product
D)quotient
Q2) A relationship in which both the independent and dependent variables are influenced by a causally prior control variable such that the original relationship is "explained away" by the control variable,is referred to as
A)spuriousness.
B)statistical significance.
C)percentage difference.
D)dependence.
Q3) Briefly describe the difference between a spurious and intervening relationship.
Q4) A bivariate table can have any number of dimensions.
A)True
B)False
Q5) Provide an example of an intervening relationship and describe why it is so.
Q6) Define an intervening relationship.
Page 11
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Chapter 10: The Chi-Square Test and Measures of Association
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Sample Questions
Q1) A measure of association whose value may vary depending on which variable is considered the independent variable and which the dependent variable is called a(n)
A)symmetrical measure.
B)asymmetrical measure.
C)interdependent associate.
D)dependent associate.
Q2) The degree of freedom in a bivariate table
A)is the number of cells in the table for which the expected frequencies are free to vary.
B)is the product of the number of rows and columns.
C)compensates the distortion of a bivariate table if one cell is over or undersampled.
D)with two rows and two columns is 4
Q3) Chi-square test
A)requires no assumptions about the shape of the population distribution.
B)can be applied to only nominal data.
C)can be applied to nominal or ordinal data.
D)is also referred to as the goodness-of-fit test.
Q4) Apply the five-step model of a chi-square test to a specific example.
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Chapter 11: Analysis of Variance
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Sample Questions
Q1) In an ANOVA,the population variances are assumed to be equal.
A)True
B)False
Q2) ANOVA is best suited for comparing the means of ______ group(s)at once.
A)identical
B)one
C)at least two
D)deviant
Q3) The between-group sum of squares
A)measures differences in variance between the groups.
B)is the sum of squared deviation between each sample mean to the overall mean score.
C)is calculated using \( \sum\left(Y_{i}-\bar{Y}_{k}\right)^{2} \) .
D)is the amount of variation in the dependent variable that can be attributed to the independent variable.
Q4) What is the null hypothesis when using ANOVA procedures?
A) \( Y_{1}=Y_{2} \)
B) \( \mu_{1}=\mu_{2} \)
C) \( Y_{1}=Y_{2}=Y_{3 \ldots}=Y_{n} \)
D) \( \mu 1=\mu 2=\mu 3 \ldots=\mu n \)
Page 13
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Chapter 12: Regression and Correlation
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Sample Questions
Q1) What is the total sum of squares?
A)The sum of the squared deviations from the mean
B)The sum of the squared deviations from the regression line
C)The difference between the sum of the squared deviations from the mean and the sum of the squared deviations from the regression line
D)The effect of two or more variables on the independent variable
Q2) Compare ANOVA and regression.
Q3) The residual is the difference between the predicted \( \hat{Y} \) and the observed Y,i.e. \( e=\hat{Y}-Y \) .
A)True
B)False
Q4) In the linear regression equation Y = a + b (X)
A)X = the score of the independent variable
B)a = the Y-intercept
C)b = the slope of the regression line
D)Y = the observed score of the dependent variable
Q5) Residual sum of squares, \( S S E=\sum(Y-\bar{Y})^{2} \).
A)True
B)False
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