Chapter 12 & Readings Flashcards
What method of analysis is commonly associated with grounded theory? A. Discourse analysis B. Statistical analysis C. Ethnographical analysis D. Constant comparison analysis
D
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
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
True
In general, one could say that discourse analysis focuses on how people say things as opposed to what they say.
A. True
B. False
True
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
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
What are some theoretical frameworks commonly used in qualitative data analysis?
A. Postpositivism
B. Postpragmatism
C. Postmodernism
D. Feminist theory and indigenous theory
D
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
Which mixed methods data analysis strategy that you use, is partially determined by the mixed methods design that is employed.
A. True
B. False
True
According to your textbook, generalizability is only a concern in the interpretation of quantitative data
A. True
B. False
False
The type of statistical analysis focused on describing, summarizing, or explaining a set of dat
Descriptive statistics
The type of statistical analysis focused on making inferences about populations based on sample data
Inferential statistics
A set of data, where the rows are“cases” and the columns are “variables”
Data set
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
frequency distribution
Numerical value expressing what is typical of the values of a quantitative variable
Measure of central
tendency
Mode
most frequently occurring number
Median
The center point in a row of numbers
Mean
average
Numerical value expressing how spread out or how much variation is present in the values of a quantitative variable
Measure of variability
The highest number minus the lowest number
Range
The average deviation of data values from their
Variance
The square root of the variance
Standard Deviation
is an approx- imate indicator of the average distance that your data values are from their mean.
A theoretical distribution that follows the 68,95, 99.7 percent rule
A bell shape
Normal distribution
Rule stating percentage of cases falling within 1, 2, and 3 standard deviations from the mean on a normal distribution
68, 95, 99.7
percent rule
A score that has been transformed into standard deviation units
z-score
rawscore - mean X - X
z-score = standard deviation = SD
The difference between two means in the variables’ natural units
Unstandardized difference between means
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
Sampling distribution
The theoretical probability distribution of the means of all possible samples of a particular size selected from a population
Sampling distribution of the mean
The standard deviation of a sampling distribution
Standard Error
Point Estimation
Use of the value of a sample statistic as one’s estimate of the value of a population parameter
Interval Estimation
Placement of a range of numbers around a point estimate
Confidence Interval
An interval estimate inferred from sample data that has a certain probability
of including the true population parameter
The branch of inferential statistics focused on determining when the null hypothesis can or cannot be rejected in favor of the alternative hypothesis
Hypothesis testing
Null Hypothesis
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.
_________________ 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).
alternative hypothesis
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.
Alpha level
Level of Significance
Or it is when you reject the null and go with the alternative`
Independent Samples t test
The significance test of the difference between two means that uses the t probability distribution
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.
t distribution
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
Critical REgion
The likelihood of the observed value (or a more extreme value) of a statistic, if the null hypothesis were true
Probability Value or pvalue
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
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.
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).
statistically significant
Independent samples t test
Used to determine if the difference between the means of two groups is statistically significant
An index of magnitude or strength of relationship
Effect size indicator
effect size indicator tells you how much variance in the dependent variable is uniquely explained by the independent or predictor variable
partial eta squared
an alternative hypothesis that includes a not equal to sign ( ).
nondirectional alternative hypothesis
contains either a greater than sign (>) or a less than sign (
directional alternative
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.
directional alternative hypothesis
What are the 5 steps in hypothesis testing with decision making rules?
- state the null & the alter.
- Set the alpha level
- select the statistical test to be used
- Conduct the test and obtain the p value
- Compare the p value to the alpha level
If p value is less than or equal to the alpha level, what do you do?
reject the null and tentatively accept the alternative
If p value is greater than alpha?
Fail to reject the null and the research is not statistically significant
What is a Type I error/
the researcher rejects a true null
What is a type 2 error?
failure to reject a false null
used to compare two or more group means for statistical significance
One Way analysis of variance or ANOVA
post hoc tests
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
Analysis of covariance (also called ANCOVA
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”)
Statistical test used when you have one quantitative DV and two categorical IVs
Two-way analysis of variance
is used when you have one quantitative dependent variable and one within-participants independent variable
One-way repeated measures analysis of variance
Statistical test used to determine if a regression coefficient is statistically significant
t test for regression coefficients
used to determine whether a relationship observed in a contingency table is statistically significant
chi-square test for contingency tables
Two major branches in the field of inferential statistics are
Estimation
hypothesis testing
The number of values that are“free to vary”; it’s used when computing a statistic to be used in inferential statistics
Degrees of freedom
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
One-way analysis of variance (one way- ANOVA)
Used if you have 3 or more means this is required
It is a follow up.
Post hoc tests
Statistical test that is used when you have one quantitative dependent variable and one within-participants independent variable.
Analysis of Covariance
ANCOVA
Statistical test that is used when you have a quantitative dependent variable and two categorical independent variables.
Two-way analysis of variance (two-way ANOVA)
Statistical test that is used when you have one quantitative dependent variable and one within-participants independent variable.
One-way repeated measures analysis of variance
The ——————— uses the t distribution to test the significance of the regression coefficients obtained in regression analysis.
t test for regression coefficients
The_____________ is used to determine whether a relationship observed in a contingency table is statistically significant.
chi-square test for contingency tables
