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IDE 660 > Chapter 12 & Readings > Flashcards

Chapter 12 & Readings Flashcards

1
Q 
What method of analysis is commonly associated with grounded theory?
 A. Discourse analysis
 B. Statistical analysis
 C. Ethnographical analysis
   D. Constant comparison analysis
A

D

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2
Q

Which of the following is used for group differences evaluation questions?
A. t test for independent samples
B. Pearson product-moment coefficient of correlation
C. Mean and variance
D. Range

A

A

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3
Q

In generic discourse analysis, evaluators tend to focus on looking for patterns and structures used in language (rather than focusing on identifying key themes in the data).
A. True
B. False

A

True

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4
Q

In general, one could say that discourse analysis focuses on how people say things as opposed to what they say.
A. True
B. False

A

True

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5
Q

How are codes usually developed in qualitative data analysis?
A. Careful, reflective reading of transcripts.
B. Modifying codes developed in similar studies published in the literature
C. Using preexisting codes from a master codebook
D. None of the above

A

A

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6
Q 
Who are the researchers who initiated grounded theory as a systematic method?
   A. Glaser and Strauss
 B. Campbell and Shadish
 C. Pope and Wallace
 D. Patton and Stake
A

A

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7
Q

What are some theoretical frameworks commonly used in qualitative data analysis?
A. Postpositivism
B. Postpragmatism
C. Postmodernism
D. Feminist theory and indigenous theory

A

D

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8
Q

What does critical discourse analysis rely on?
A. It uses the transformative theoretical lens to bring meaning to the data.
B. Analyzing the data using statistical analysis.
C. It mostly uses classical pragmatism.
D. None of the above.

A

A

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9
Q

Which mixed methods data analysis strategy that you use, is partially determined by the mixed methods design that is employed.
A. True
B. False

A

True

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10
Q

According to your textbook, generalizability is only a concern in the interpretation of quantitative data
A. True
B. False

A

False

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11
Q

The type of statistical analysis focused on describing, summarizing, or explaining a set of dat

A

Descriptive statistics

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12
Q

The type of statistical analysis focused on making inferences about populations based on sample data

A

Inferential statistics

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13
Q

A set of data, where the rows are“cases” and the columns are “variables”

A

Data set

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14
Q

A________ is a systematic arrangement of data values in which the unique data values are rank ordered and the frequencies are provided for each of these values

A

frequency distribution

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15
Q

Numerical value expressing what is typical of the values of a quantitative variable

A

Measure of central

tendency

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16
Q

Mode

A

most frequently occurring number

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17
Q

Median

A

The center point in a row of numbers

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18
Q

Mean

A

average

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19
Q

Numerical value expressing how spread out or how much variation is present in the values of a quantitative variable

A

Measure of variability

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20
Q

The highest number minus the lowest number

A

Range

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21
Q

The average deviation of data values from their

A

Variance

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22
Q

The square root of the variance

A

Standard Deviation

is an approx- imate indicator of the average distance that your data values are from their mean.

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23
Q

A theoretical distribution that follows the 68,95, 99.7 percent rule
A bell shape

A

Normal distribution

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24
Q

Rule stating percentage of cases falling within 1, 2, and 3 standard deviations from the mean on a normal distribution

A

68, 95, 99.7

percent rule

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25
Q

A score that has been transformed into standard deviation units

A

z-score
rawscore - mean X - X
z-score = standard deviation = SD

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26
Q

The difference between two means in the variables’ natural units

A

Unstandardized difference between means

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27
Q

The theoretical probability distribution of the values of a statistic that would result if you selected all possible samples of a particular size from a population

A

Sampling distribution

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28
Q

The theoretical probability distribution of the means of all possible samples of a particular size selected from a population

A

Sampling distribution of the mean

29
Q

The standard deviation of a sampling distribution

A

Standard Error

30
Q

Point Estimation

A

Use of the value of a sample statistic as one’s estimate of the value of a population parameter

31
Q

Interval Estimation

A

Placement of a range of numbers around a point estimate

32
Q

Confidence Interval

A

An interval estimate inferred from sample data that has a certain probability
of including the true population parameter

33
Q

The branch of inferential statistics focused on determining when the null hypothesis can or cannot be rejected in favor of the alternative hypothesis

A

Hypothesis testing

34
Q

Null Hypothesis

A

a statement about a pop- ulation parameter; typically, it states that there is no relationship between the inde- pendent and dependent variables in the population.

35
Q

_________________ is the logical opposite of the null hypothesis (i.e., stating that there is a relationship between the independent and dependent variables in the population).

A

alternative hypothesis

36
Q

The___________ or ___________ use set by the researcher usually at .05 and it is the point at which the researcher would conclude that the observed value of the sample statistic is sufficiently rare under the assumption of the true null hypothesis.

A

Alpha level
Level of Significance

Or it is when you reject the null and go with the alternative`

37
Q

Independent Samples t test

A

The significance test of the difference between two means that uses the t probability distribution

38
Q

the __________ looks a lot like a normal curve; it’s just a little flatter and a little more spread out than the normal curve. Just like the normal curve, the t distribution has a mean of zero, is symmet- rical, is higher in the center, and has a “left tail” and a “right tail” that represent rare events.

A

t distribution

39
Q

he area on a null hypothesis sampling distribution where the observed value of the statistic, if it fell in this area, would be considered a rare event

A

Critical REgion

40
Q

The likelihood of the observed value (or a more extreme value) of a statistic, if the null hypothesis were true

A

Probability Value or pvalue

41
Q

The_______ is a value between 0 and 1, and it indicates the proportion of the area in the sampling distribution that lies at or beyond the value of your test statistic value

A

p value

  • The closer the p value is to zero, the less likely your test result would be if the null hypothesis were true. Therefore, a very small p value provides the evidence you need to reject the null hypothesis. A very small p value means that the value of your sample statistic would be a rare event if the null hypothesis were true.
42
Q

which means the finding (e.g., such as an observed difference between two means) is very likely a real relationship (i.e., not due to chance).

A

statistically significant

43
Q

Independent samples t test

A

Used to determine if the difference between the means of two groups is statistically significant

44
Q

An index of magnitude or strength of relationship

A

Effect size indicator

45
Q

effect size indicator tells you how much variance in the dependent variable is uniquely explained by the independent or predictor variable

A

partial eta squared

46
Q

an alternative hypothesis that includes a not equal to sign ( ).

A

nondirectional alternative hypothesis

47
Q

contains either a greater than sign (>) or a less than sign (

A

directional alternative

48
Q

If the researcher uses a ___________ and a large difference is found in the opposite direction, he or she can not conclude that a relationship exists in the population. That’s the rule of ____________—even if you find a large difference you must conclude that the difference is not statistically significant if it’s in the opposite direction from the one you hypothesized.

A

directional alternative hypothesis

49
Q

What are the 5 steps in hypothesis testing with decision making rules?

A
  1. state the null & the alter.
  2. Set the alpha level
  3. select the statistical test to be used
  4. Conduct the test and obtain the p value
  5. Compare the p value to the alpha level
50
Q

If p value is less than or equal to the alpha level, what do you do?

A

reject the null and tentatively accept the alternative

51
Q

If p value is greater than alpha?

A

Fail to reject the null and the research is not statistically significant

52
Q

What is a Type I error/

A

the researcher rejects a true null

53
Q

What is a type 2 error?

A

failure to reject a false null

54
Q

used to compare two or more group means for statistical significance

A

One Way analysis of variance or ANOVA

55
Q

post hoc tests

A

Follow-up test to one-way ANOVA when the categorical IV has three or more levels; used to determine which pairs of means are significantly different

*to determine which of the means are significantly different

56
Q

Analysis of covariance (also called ANCOVA

A

used when you have a quanti- tative dependent variable and a mixture of categorical and quantitative independent variables

used when you have a one quantitative DV and a mixture of categorical and quantitative IVs (the quantitative IV is called a“covariate”)

57
Q

Statistical test used when you have one quantitative DV and two categorical IVs

A

Two-way analysis of variance

58
Q

is used when you have one quantitative dependent variable and one within-participants independent variable

A

One-way repeated measures analysis of variance

59
Q

Statistical test used to determine if a regression coefficient is statistically significant

A

t test for regression coefficients

60
Q

used to determine whether a relationship observed in a contingency table is statistically significant

A

chi-square test for contingency tables

61
Q

Two major branches in the field of inferential statistics are

A

Estimation

hypothesis testing

62
Q

The number of values that are“free to vary”; it’s used when computing a statistic to be used in inferential statistics

A

Degrees of freedom

63
Q

is used to compare two or more group means for statistical significance. Statistical test used when you have one quantitative DV and one categorical IV

A

One-way analysis of variance (one way- ANOVA)

64
Q

Used if you have 3 or more means this is required

It is a follow up.

A

Post hoc tests

65
Q

Statistical test that is used when you have one quantitative dependent variable and one within-participants independent variable.

A

Analysis of Covariance

ANCOVA

66
Q

Statistical test that is used when you have a quantitative dependent variable and two categorical independent variables.

A

Two-way analysis of variance (two-way ANOVA)

67
Q

Statistical test that is used when you have one quantitative dependent variable and one within-participants independent variable.

A

One-way repeated measures analysis of variance

68
Q

The ——————— uses the t distribution to test the significance of the regression coefficients obtained in regression analysis.

A

t test for regression coefficients

69
Q

The_____________ is used to determine whether a relationship observed in a contingency table is statistically significant.

A

chi-square test for contingency tables

IDE 660 (14 decks)

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