Study Questions Creating Examining a Database 1 What is a database 2 by jly17328

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									                                     Study Questions
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                             Creating & Examining a Database


 1. What is a database?

 2. What is a spreadsheet?

 3. What two things should the analyst examine about the data prior to
    analysis?

 4. What is a database code sheet? What kinds of information should be
    recorded in the code sheet?

 5. What is the difference between measurement and categorical variables (i.e.
    metric and nonmetric variables)

 6. Using examples, define and contrast each of the following scales of
    measurement: nominal, ordinal, interval, and ratio.

 7. Prior to analysis of the data, each variable should be examined for data
    quality and distributional dynamics. What specific things should the analyst
    look for?

 8. What problems result from missing data at the univariate and multivariate
    levels?

 9. In a large database, how can missing data be identified?

10. Identify and explain various ways to deal with the problem of missing data?

11. What is a statistical outlier? Why are such cases problematic?

12. How can outliers be identified and the cases remedied?

13. What is a box-whisker plot?

14. What is a stem and leaf plot?

15. What is a scatterplot?

16. What is the difference between the statistical concepts of central tendency
    and variability?

17. What is a frequency distribution?



         Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
18. What is a histogram?

19. What is a pie chart?

20. What is meant by the statistical concept of skew?

21. What is meant by the statistical concept of kurtosis?

22. What is meant by the modality of a distribution?

23. What is meant by the reliability of a measure?

24. What is meant by the validity of a measure?

25. What is the difference between a sample and a population? What symbols
    are used to signify a sample and a population?

26. What is a statistical inference?

27. What is the difference among univariate, bivariate, and multivariate
    statistics?




         Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
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                                         Descriptive Tools


 1. What is a frequency distribution and describe ways that such a distribution
    can be presented numerically and graphically?

 2. Describe the procedures used to convert a measurement variable to a
    frequency distribution and the rationale for these procedures.

 3. Proportions, percentages, and/or cumulative frequencies, proportions and
    percentages can be added to the frequency table of a measurement
    variable. How is this done and in what ways does this add to the
    informational value of a frequency table?

 4. Describe the procedures used to determine a percentile rank from a
    frequency table in which the frequencies of a measurement variable have
    been recorded in class intervals. Give an example to illustrate the
    procedures.

 5. What are rates and ratios and describe how these data conversions can be
    useful to the analyst? Present an example of these statistical procedures.

 6. In what way can a percent change statistic be misleading?

 7. What is a cross-tabulation table and what is the purpose served a creating
    such a table?

 8. What rules should be followed in percentaging a cross-tabulation table?

 9. Using an example, describe the procedures used in constructing a pie chart.

10. What is the difference between a bar graph and a histogram? Give an
    example of each.

11. Distinguish between a histogram, frequency polygon, and an ogive curve.
    Present examples of each.

12. What phenomena are explored in a time series plot? Give an example.

13. What is a scatterplot and what kinds of research questions is it designed to
    answer? Give an illustration.

14. What is a box whisker plot? How is one constructed and interpreted. What
    kinds of questions can be answered with such a plot?



        Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
15. What is a stem and leaf plot? How is it constructed? What kinds of questions
    can be answered with such a plot?




        Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
                                     Study Questions
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                                Measuring Central Tendency


 1. 1.Why is the answer to the question “What’s average?” complicated rather
    than simple?

 2. Contrast the mode, median and the mean. Under what circumstances are
    they the same and different in value.

 3. What criteria should be considered in choosing between the mean and the
    median to describe central tendency?

 4. How is the median of a distribution computed?

 5. How is the mean of a distribution computed?

 6. What is statistically peculiar about the deviations and squared deviations
    about the mean?

 7. What measures of central tendency are appropriate to use with variables
    measured on different scales of measurement?

 8. Illustrate the relationship between different measures of central tendency
    relative to distributions manifesting different forms of skew.

 9. Relative to measuring central tendency, what is meant by the term “resistant
    statistic”?

10. What assumptions are made in calculating the mode, mean, and median
    from grouped data?

11. Under what circumstances might one compute a 5% trimmed mean or any
    of the M-estimators as measures of central tendency? What caveats should
    be considered in using these statistics?

12. What is the geometric mean? How is it calculated? Under what
    circumstance should it be used?

13. What is the harmonic mean? How is it calculated? Under what circumstance
    should it be used?




        Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
14. What problems are encountered in averaging the means, proportions,
    and/or percentages derived from different samples? How can these
    problems be remedied?




       Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
                                       Study Questions
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                                      Measuring Variability


 1. Why are the questions of central tendency and variability the two most
    informative questions that can be asked about a variable?

 2. Why is the range a very limited measure of variability? Limited relative to
    what?

 3. What is the difference between the mean deviation and the standard
    deviation?

 4. What are the variance and the standard deviation? How are they
    calculated?

 5. What is the difference between a deviation and raw score equation? Why
    have two ways for calculating the same statistic?

 6. What is the correction for sample size in computing the variance and the
    standard deviation? Why is this necessary and what purpose is served by
    this correction?

 7. What is the IQR? How is it calculated and interrupted? What measure of
    central tendency is the IQR usually associated with?

 8. What is the pseudo standard deviation and how can it be used to compare
    the standard deviation and the IQR of the same distribution?

 9. As a rule of thumb, how is the range related to the standard deviation?

10. What is meant by the concept of moments about the mean? How is this
    used in the calculation of skew and kurtosis?

11. What is the coefficient of variability? How is it calculated and what kind of
    question is it designed to answer? Give an illustration.




        Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
                                          Study Questions
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                                         Probability Theory

 1. Define and contrast the concepts of theoretical and relative frequency
    probability? Present examples of each.

 2. Define and give examples of each of the following terms: the complement of
    an event, mutually exclusive events, independent events, and conditional
    probability.

 3. What is the addition rule of probability? Give an example of the application
    of this rule.

 4. What is the multiplication rule of probability? Give an example of the
    application of this rule.

 5. Describe and illustrate how the multiplication rule can be used to determine
    the independence of events in a two-way cross-tabulation table.

 6. What is a binomial distribution and what kind of phenomenon can it be used
    to model?

 7. Illustrate with examples the difference between the histograms of two
    binomial phenomenon; in one of which p=q=0.5, and in the other pq.

 8. What is Pascal’s triangle?

 9. What is the relationship between the binomial distribution and the normal
    distribution?

10. If a variable is normally distributed, what is the relationship between the
    mean and standard deviation of the distribution and the normal distribution?

11. What is a standard score (Z) and how is it used to relate the values of a
    normally distributed variable to the probability dynamics of a normal
    distribution?

12. If a variable is normally distributed, how can the normal distribution be used
    to determine the percentile rank of a case in the distribution?

13. What statistical tools can be used to determine if a variable is normally
    distributed Illustrate your answer with an example.

14. What is a normally probability plot? What can one tell from such a plot about
    the shape of the distribution of a variable?



         Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
                                   Study Questions
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                           Sampling Theory & Standard Errors


 1. What is statistical inference and what are the five critical questions in the
    inferential process?

 2. What are the advantages of studying a sample vis-à-vis an entire
    population?

 3. What is the difference between probability and non-probability sampling
    techniques?

 4. Present an example of the procedure used to select a simple random
    sampling.

 5. Define and contrast stratified and quota sampling.

 6. What is cluster sampling and how is it related to multistage sampling?

 7. Give an example of systematic sampling.

 8. Define and contrast accidental and purposive sampling. What are the
    advantages and disadvantages of each technique?

 9. How might snowball sampling be used? Give an example.

10. What factors should be considered in determining the adequacy of the size
    of a sample?

11. What does it mean to say that a sample is representative of a population
    and how might one determine if a sample is representative of a population?

12. What is the standard error of the mean, How is it used to determine the
    accuracy in generalizing a sample mean to a population parameter?

13. What is a table of random numbers and how can such a table be used in
    selecting a random sample from a population? Describe the process.

14. What is a confidence interval of a mean (e.g. 95% or 99%)? How is this
    interval calculated? How are confidence intervals used in statistical
    inference?

15. What is an empirical sampling distribution of a statistic, say the mean?




         Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
16. What is the Central Limit Theorem and what are the implications of this
    theorem in statistical inference?

17. How is the standard error of the mean related to the standard deviation of
    the sampling distribution of the mean?

18. How does the sampling distribution of the mean change as the sample size
    becomes smaller? Why does this happen?

19. What is a t distribution? How is this related to the sampling distribution of the
    mean?

20. Compare and contrast the t and normal distributions.

21. Relative to the confidence interval of the mean, what is significant about the
    standard scores (Z) of 1.96 and 2.58?

22. What assumptions can be made about the sampling distributions of
    proportions and percentages as the size of the samples become smaller?




         Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
                           Study Questions
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          Differences Between Sample Means and Proportions


1. In the context of statistical inference, define and contrast the following
   concepts: research and null hypotheses, acceptance and rejection of the
   null hypothesis, Type I & II errors, and alpha and beta.

2. Relative to the Central Limit Theorem, what can be assumed about the
   sampling distribution of the difference between sample means?

3. What does the standard error of the difference between sample means
   describe, and how does this relate to a t distribution and a normal
   distribution?

4. What type of research question is a t-test on the difference between
   sample means designed to answer? What are the assumptions of this t-
   test?

5. In the context of differences between sample means, what does the
   concept of statistical significance mean?

6. If the null hypothesis states that two sample means come from two
   populations with equal means, and the null hypothesis is rejected at p 
   0.05, what does this mean in terms of statistical inference and the
   probability of being wrong?

7. What is the importance of the assumption of homogeneity of variance in a
   t-test of the difference between sample means?

8. How are error bar charts used in conducting a t-test on the difference
   between sample means?

9. What difference does it make in conducting a t-test on the difference
   between sample means if the means are independent or paired?

10. What is the Z test for the difference between sample proportions?

11. In statistical inference, what is the difference between one- and two-tailed
    test of significance?




     Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
                                       Study Questions
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                                      Analysis of Variance


 1. What is the problem in performing multiple t-tests contrasting the means of
    multiple groups?

 2. What is mean by the concept of the inflation of alpha? How is this
    calculated?

 3. Define and explain the concept of the partitioning of sums of squares in
    analysis of variance. Show the equations for the calculation of the total,
    between, and within sums of squares.

 4. What are the degrees of freedom for the between and within sums of
    squares.

 5. What kind of question is a one-way ANOVA designed to answer? Give an
    example.

 6. What information is included in an ANOVA table?

 7. What does an F ratio indicate in analysis of variance?

 8. What is the null hypothesis in a one-way ANOVA?

 9. What is the assumption of homogeneity of variance in ANOVA?

10. What are post hoc multiple comparison tests? How are they used in
    conjunction with ANOVA and why are they used instead of multiple t-tests?

11. What is Tukey’s HSD and how is this statistical test used?

12. What is the difference between a one-way ANOVA and a factorial ANOVA?

13. Give an example of a factorial ANOVA and in the context of the example,
    explain what is meant by the main effects and interaction terms.

14. Draw a series of graphs showing various combinations of significant and
    non-significant main effects and interaction terms in a 2x3 two-way factorial
    design.

15. If the interaction term in a two-way ANOVA is significant, how does one
    interpret the main effects?




        Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
16. Describe various ways that extraneous variables can be dealt with in
    ANOVA designs.

17. What is analysis of covariance?

18. If the covariate is not significant in analysis of covariance, what does this
    mean and what is the implication on the mean differences among the groups
    in the ANOVA design?

19. What is the practical limiting factor in increasing the complexity of a factorial
    ANOVA design by adding additional independent variables?

20. Present an example of a 2x3x3, three-way factorial design? Identify the
    various main effects and interaction terms in your example.




         Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
                                      Study Questions
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                                   Nonparametric Statistics


1.    What kind of question is a one-way chi-square test designed to answer?

 1. How are expected frequencies determined in a one-way chi-square test?

 2. How is the significance of a chi-square statistic determined?

 3. How many degrees of freedom are there in a one-way chi-square test?

 4. What is the difference between a one- and two-way chi-square test?

 5. How are the expected frequencies determined in a two-way chi0-square
    test?

 6. In a chi-square test, what is the problem of small expected frequencies?

8.    How can the problem of small expected frequencies be addressed in a
      chi-square test?

 7. What is Yates’s correction and how does it work?

 8. How is Fisher’s exact probability test used?

 9. What kind of question is the median test designed to answer and what is the
    null hypothesis tested?

10. Relative to the Mann-Whitney U test, what is the limitation of the median
    test?

11. What kind of research question is the Mann-Whitney U test designed to
    answer and what is the null hypothesis tested?

12. What is the relationship between the Mann-Whitney U test and the normal
    distribution?

13. What kind of research question is the Kruskal-Wallis one-way analysis of
    variance test designed to answer and what is the null hypothesis tested?




        Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
                             Study Questions
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               Pearson Product-Moment Correlation Coefficient


1.    What does a correlation coefficient measure?

2.    How is a correlation coefficient scaled?

3.    Using examples, describe and graphically illustrate with scatterplots
      positive and negative correlations.

4.    If the relationship between tow variables is not linear, how might a Type II
      error be made in computing a Pearson correlation coefficient on the data?
      Present a graphic illustration.

5.    How is the significance of a correlation coefficient determined? What is the
      null hypothesis tested?

6.    What is the coefficient of determination and how is it interpreted?

7.    What is the coefficient of nondetermination and how is it interpreted?

8.    What assumptions does the Pearson correlation coefficient make?

9.    What is an intercorrelation matrix and what are the caveats that one
      should keep in mind in interpreting such a matrix?

10.   What is the difference between a correlation coefficient and a partial
      correlation coefficient? Present an example to illustrate your answer.

11.   What is a multiple partial correlation coefficient? Present an example to
      illustrate your answer.




       Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
                                        Study Questions
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                                       Linear Regression


1.    What kind of question is linear regression designed to answer? Give an
      example.

2.    what are the assumptions of linear regression?

3.    Why is linear regression called “linear”?

4.    How can a scatterplot be used in linear regression analysis?

5.    What is the equation of a straight line? Illustrate the elements of the
      equation of a straight line in a graph.

6.    What is meant by a “best fit” straight line in regression analysis?

7.    How is the constant and the regression coefficient of a linear regression
      equation interpreted?

8.    Given the regression equation Y = 2 + 4X, how would one plot this
      equation? Illustrate with a graph.

9.    In regression, what is meant by a residual?

10.   How are sums of squares partitioned in regression analysis?

11.   What are the equations for the total, regression, and error sums of
      squares?

12.   Graphically depict the concept of the partitioning of sums of squares in
      regression analysis?

13.   What is the algebraic relationship between the coefficient of determination
      and the regression sum of squares?

14.   How is analysis of variance used to determine the significance o0f the
      regression sum of squares? What is the null hypothesis tested in this
      ANOVA?

15.   How is a t-test used to determine the significance of a regression
      coefficient? What is the null hypothesis tested?




       Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
16.   In generalizing a regression coefficient to the population parameter, how is
      a 95% confidence interval used?

17.   What does regression analysis assume about the residuals?

18.   What is residual analysis? What does one look for in such analysis and
      what are the various statistical tools used in residual analysis?

19.   How does standardizing the residual and predicted values help in residual
      analysis? Illustrate with a scatterplot?

20.   What are standardized residuals and predictions?

21.   What is multiple linear regression and how does it differ from bivariate
      regression?




       Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
                             Study Questions
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                   Nonparametric Correlational Techniques


1. What is the difference between nonparametric correlational techniques
   and other methods for determining correlations?

2. What type of research question is the Spearman rank-order correlation
   coefficient rho designed to answer?

3. What assumptions does rho make?

4. What is the null hypothesis in computing rho?

5. Can rho take on positive or negative values? How are these interpreted?

6. Can rho be used with one or two metric variables? If so how?

7. In computing rho, how does one deal with tied ranks?

8. What is the difference between a one-tailed and two-tailed hypothesis in
   testing rho?

9. What type of research question is the Goodman’s & Kruskal’s gamma
   designed to answer?

10. What assumptions does gamma make?

11. What is the null hypothesis in computing gamma?

12. Can gamma take on positive or negative values? How are these
    interpreted?

13. Can gamma be used with one or two metric variables? If so how?

14. How is a normal distribution or a t distribution used in determining the
    significance of gamma?

15. What type of research question is the phi coefficient designed to answer?

16. What assumptions does phi make?

17. What is the null hypothesis in computing phi?

18. Can phi take on positive or negative values? If not, why not?



     Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
19. Can phi be used with one or two metric variables? If so how?

20. What is the relationship between phi and chi-square?

21. How is the significance of phi tested?

22. What type of research question is the contingency coefficient C designed
    to answer?

23. What assumptions does C make?

24. What is the null hypothesis in computing C?

25. Can C take on positive or negative values? If not, why not?

26. Can C be used with one or two metric variables? If so how?

27. What is the relationship between C and chi-square?

28. How is the significance of C tested?

29. What is the relationship between C and phi?

30. What is the computational limitation of C?

31. What type of research question is Cramér’s V designed to answer?

32. What assumptions does V make?

33. What is the null hypothesis in computing V?

34. Can V take on positive or negative values? If not, why not?

35. Can V be used with one or two metric variables? If so how?

36. What is the relationship between V and chi-square?

37. How is the significance of V tested?

38. What type of research question is Guttman’s lambda designed to answer?

39. What assumptions does lambda make?

40. What is the null hypothesis (es) in computing lambda?




     Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University
41. Why are two lambdas computed depending upon which variable is the
    independent and which the dependent variable?

42. Can lambda take on positive or negative values? If not, why not?

43. Can lambda be used with one or two metric variables? If so, how?

44. Lambda is an asymmetrical statistic. What does this mean?

45. What is meant by the proportionate reduction of error in computing
    lambda?




     Study Questions: Charles M. Friel Ph.D., Criminal Justice Center, Sam Houston State University

								
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