Quantitative Data Analysis Flashcards
1
Q
What is data analysis?
A
- Methodology by which individual data points are rendered into meaningful and intelligible information
- Product of data analysis in research is knowledge
- Techniques will differ based on design (descriptive or inferential stats)
- Analysis determines trends and patterns of relationships based on the data
2
Q
What is inferential statistics?
A
- Allows researchers to estimate how reliably they can make predictions and generalize findings on the basis of the data (inference = conclusion based on evidence and reasoning)
- Use of a stat created from a smaller group to draw a conclusion about a population via math processes and logic to test hypothesis about a population on a sample
- Allows researchers to test hypotheses about a population using data obtained from probability and non-probability samples
- Parametric or non-parametric
3
Q
What is descriptive stats?
A
- Description and/or summarization of sample data, reduced into manageable proportions
- Allow researchers to arrange data visually to display meaning and to help in understanding the sample characteristics and variable under study
- In some studies, descriptive stats may be the only results sought from stat analysis
4
Q
What is the purpose of descriptive stats?
A
- Reduce data to manageable proportions by summarizing them
- Measure of central tendency; scatter plot; range; mean; average; percentages
5
Q
What is a level of significance (alpha level)?
A
- Probability of making a type 1 error (0.05)
- The smaller the better, anything greater means it isn’t significant
- Researcher willing to accept that if study was done 100 times, decision to reject the null hypothesis would be wrong 5 times out of those 100 trials
- Can set probability at 0.01 if wanting a smaller risk of rejecting a true null hypothesis
6
Q
What is the mean and median?
A
- Measure of an average score, most frequently reported in stats
- Median (score in middle of list) best indication of a typical score that accounts for outliers
- Mode is the most frequent score
7
Q
How do we choose a statistical test?
A
Appropriate stat procedure is a function of:
1) The research design
2) The level of data provided by the data collection instrument
3) Sampling procedure
8
Q
What designs might we see in descriptive stats?
A
- Exploratory descriptive designs (case studies)
- Correlational designs
9
Q
What designs might we see in inferential stats?
A
- Correlational designs
- Comparative designs
- Experimental and quasi-experimental designs
10
Q
What is nominal measurement?
A
- The assignment of numbers to simply classify characteristics into categories
- Sometimes called “dummy variables” (Used to quantify variables)
- E.g. Gender, Marital status, Religious affiliation. If you are a female you get a 1, male a 0, etc.
11
Q
What is ordinal measurement?
A
- Permits the sorting of objects on the basis of their standing on an attribute relative to each other
- A higher score is better (or worse), but how much better (or worse) is not known (Class ranking, Likert scale responses)
- E.g. 1 if you strongly agree, 5 if you strongly disagree.
12
Q
What is interval/ratio measurement?
A
- Determines both the rank ordering of objects on an attribute and the distance between those objects
- E.g. scores on an intelligence test; temp/BP, height/length
13
Q
What is the range?
A
Describes the variability or differences between the highest and lowest scores
14
Q
What is standard deviation?
A
Another indication of variability, calculated from the average differences from the mean
15
Q
What is a p-value?
A
- Explains statistical significance
- Needs to be p<0.05 or <0.01 to have a significance; the smaller indicates that results are likely d/t experimental intervention, not chance
- This # states the researcher admits that there could a 5% chance the results found in a study are due to chance alone
16
Q
Describe the relationship between stat significance and clinically meaningful results:
A
- Results can be stat significant but not clinically significant or important, and vice versa
- Findings should be stat significant and clinically meaningful before considering them in practice
17
Q
What is psychometrics?
A
- Theory of measurement involved in development of measuring tools
- Psychometric assessment refers to eval of validity and reliability of an instrument before making it available for use
- Often indicated by Cronbach’s alpha (co-efficient alpha)
- Reliability of 0.80 is considered lowest acceptable coefficient for a well-developed tool
18
Q
What is one-tailed test of significance?
A
- Used with a directional hypothesis (extreme stat values occur on a single tail of the normal curve)
- One-tailed more powerful but requires more knowledge to predict direction
- Two-tailed test of significance occurs with a non-directional hypothesis and assumes extreme scores occur in either tail of the normal curve
19
Q
What is parametric?
A
- More powerful** and more flexible than non-parametric
- Assumes normal distribution of data (e.g. random sample)
- Used with interval and ratio variables
- Goes with our probability sampling
- E.g. t-test, ANOVA
20
Q
What is non-parametric?
A
- Less powerful **
- Not based on the estimation of population parameters
- Does not assume normal distribution within sample (e.g. not random sample)
- Used with nominal or ordinal variables
- Non-p goes with our non-probability sampling
- E.. Chi-square test
21
Q
What is confidence intervals?
A
- An estimated range of values that provides a measure of certainty about the sample findings
- Most commonly reported in research is a 95% degree of certainty, meaning 95% of the time, the findings will fall within the range of values given as the CI
- Gives an idea of how people were answering, the range of scores, etc.
22
Q
How do we critique data analysis?
A
- Are data analysis procedures clearly described?
- Were appropriate statistical tests used given the level of measurement that is used to describe each of the major variables?
- Are results presented in an understandable way? Is it presented as just a table or is there actual paragraphs discussing it?
- Are the results significant?
23
Q
How do researchers present their findings?
A
- Results section present the raw data and analysis
- Discussion section interprets the results and findings (what does the results tell us, limitations, implication for practice)
