Analysis of data Ch.12.

The flashcards below were created by user lrnino on FreezingBlue Flashcards.

  1. What is content analysis mean?
    structuring unstructured data.
  2. what is a descriptive analysis?
    Describing your data. So it only pertains to your sample since it came from only your data. 

    Ex. stating your findings from the group that you studied.
  3. What is inferential analysis?
    Statistical support for your answer to your question, thus allowing you to make inferences for a general population.

    Since you have statistics to back it up, you can generalize it.
  4. What are the two basic types of analysis?
    inferential and descriptive.
  5. How can you use a dscriptive analysis on a lvl I study?
    Content analysis of unstructured data. Take it all and put into categories.
  6. How can you use a descriptive analysis on a lvl II study?
    Take findings that are specific to the group studied and look for relationships.
  7. When you use chi square as a statistical analysis, what are you doing?
    Chi square is a test that checks to see if your data is bc of chance or bc of the IV you're measuring. 

    It checks to see if there's a statistical relationship between that is expected and what is observed.
  8. Descriptive analysis is commonly used as summerized data. Usually as a frequency distribution.
  9. What does mean work well with what level of information?

    interval and ratio.
  10. What level of measurement does median work well with?

  11. What level of measurement does mode work well with?
  12. What level of measurement does SD work well with?
    interval and ratio
  13. What level of measurement does range & interquartile range work well with?
  14. What level of measurement does # of catergories work well with?
  15. What is the purpose of the histogram?
    graphically summarize the distribution of a univariate data set.
  16. What are the measures of central tendency?
    mean, median & mode
  17. What are the measures of variability?
    • range
    • SD
    • normal dsitribution (the bell curve)
  18. What is the basis for testing differences (including level II & III)?

    A) mean
    B) mode
    C) median
    A) mean
    (this multiple choice question has been scrambled)
  19. What does it mean to you if you get a normal distribution (a bell curve)?
    Means you can generalize with great certainty.
  20. +1 SD=__% cases
    +2 SD=__% cases
    +3 SD=__% cases
    • 68
    • 95
    • 99.7
  21. What is a disadvantage of the SD?
    unit specific
  22. Parametric or non-parametric tests?

    Nominal or ordinal?

    (not specific enough)
  23. Parametric or non-parametric test?

    Interval or Ratio?

    (parametric needs a lot of data. Interval and Ratio are specific enough).
  24. You have a small sample size, <30, you gonna parametric or not?
    No. sample aint big enough.
  25. What are you going to use at the nominal level?

    A) chi-square
    B) multiple regression
    C) spearman rank
    D) pearson r
    A) chi-square
    (this multiple choice question has been scrambled)
  26. What are you going to use at the ordinal level?

    A) spearman rank
    B) multiple regression
    C) pearson r
    D) chi-square
    A) spearman rank
    (this multiple choice question has been scrambled)
  27. What are you going to use at the interval/ratio level?

    A) chi-square
    B) pearson r
    C) multiple regression
    D) spearman rank
    • B) pearson r
    • C) multiple regression
  28. What inferential analysis test are you going to use for nominal levels of data?
    Fisher exact test
  29. What inferential analysis test are you going to use for ordinal levels of data?
    Mann-Whitney U or Kruskall-Wallis
  30. What inferential analysis test are you going to use for interval/ratio data?
    t-test or ANOVA
  31. What is the difference b.w. a scientific hypothesis and a null one?
    scientific is what the researcher is expecting to find.

    Null means there is no difference. So if you accept the null hypothesis, there is no difference. If you reject it, disagree that there is no difference, then there is a difference, something is making that difference and it isn't happening by "chance".
  32. Why is probability theory the basis for statistical techniques?
    They evaluate the data in an obj. way. The researcher can then look at this and decide wether is happened by "chance" or not.
  33. A type I error is a...?

    A) false positive
    B) false negative
    A) false positive
  34. A type II error is a...?

    A) false positive
    B) false negative
    B) false negative
Card Set:
Analysis of data Ch.12.
2014-04-18 00:33:15
Analysis data 12

Analysis of data Ch.12.
Show Answers: