# Unit 5: Analyzing data

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1. What are 2 categories of Quantitative statistics?
-Descriptive Statistics: Used to describe the levels and associations found in a sample

-Inferential statistics: used to estimate the probability that sample findings can be generalized to a population
2. What are 2 categories of quantitative statistics?
1: descriptive statistics- used to describe the levels and associations found in a sample. (# that tells you level or associations)

2: inferential statistics- used to estimate the probability that the levels and associations found in the sample can be generalized to a population. (what's the likelihood that the associations fit with the population?)
3. What are measures of Central tendency?
1-mean: sum of set of scores/ #of scores (avg)

2-median: score or point in a distribution above which one-half of the scores lie (score in exact middle

3-Mode: score that occurs most frequently
4. What are the measures of central tendency and their level of measurement?
Mode- Nominal- Eye color, party affiliation

Median- Ordinal- Rank in class, birth order

Mean- Interval & ratio- Speed of response, age in years
5. What is variability? And what are measures of variability?
Is the degree of spread or dispersion that characterizes a group of scores and it is the degree to which a set of scores differs from some measure of central tendency, most often the mean.

-more spread out, more variability

• Measures:
• 1- range: dif between highest and lowest score
• 1- standard deviation: the average amount that each of the individual scores varies from the mean of the set of scores.
6. What is the inferential statistic?
t is the inferential statistic. The bigger or father from 0 it is, the better. (big + or - value)
7. What is a statistical significance?
It is the p-value.

It is the degree of risk that you are willing to take that you will reject a null hypothesis when it is actually true.
8. What is the level of significance?
.01 or .05 is 1% or 5% chance you will reject the null hypothesis when it is true.
9. What is a Type I error?
Same thing as statistical significance.

-Rejecting null hypothesis when the Null is actually true.
10. When can you have no error?
When you reject the null hypothesis when the Null is actually False.

Or

When you Accept the Null hypothesis when the null it is actually true.
11. When have you made a Type II error?
If you accept the Null hypothesis when the Null is actually false.
12. What is a t-test?
A t-test is for independent means.

It tests difference between 2 means based on 2 independent, unrelated groups
13. What is a Multivariate analysis of variance (MANOVA)?
Advanced technique that examines whether group differences occur on more than one dependent variable.

Allows the researcher to assess the simultaneous effects of multiple independent variables on a single continuous dependent variable.
14. What is the analysis of variance? (ANOVA)
An independent variable with 2 or more categories -ethnicity: white, black, asian.

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 Author: xiongashely ID: 252727 Filename: Unit 5: Analyzing data Updated: 2013-12-13 20:38:19 Tags: fsos Folders: Description: analyzing data Show Answers:

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