Statistical Techniques and sampling designs (step 4 deductive research process)
5 important questions on Statistical Techniques and sampling designs (step 4 deductive research process)
What's the difference between descriptive statistics and inferential statistics?
1. Descriptive statistics: Methods of summarizing the data in an informative way.
- Measures of central tendency (mean, median, mode)
- Measures of dispersion (range, standard deviation, variance, interquartile range: you look at the 50 middle data)
2. Inferential statistics: Methods to draw conclusions (or to make inferences).
- Mean difference test
- Chi - square test
- Analysis of variance (ANOVA)
- Regression analysis
- Logit analysis
What are the four types of scales and what are the differences?
2. Ordinal: Ranked or ordered. We don't know how much between orders (more spicier: based on personal flavour).
3. Interval: Meaningful differences between values, but no natural zero point (IQ).
4. Ratio: meaningful differences and ratios between values due to a natural zero point (for example zero means "no distance" navigation).
What's the goal of a sampling design?
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Why use samples in the first place?
- Impossible to study the entire population;
- Prohibitive to study the entire population in terms of cost & speed.
When you have to determine the sampling design, as a researcher you have to choose between 2 types of sampling techniques. What are these sampling techniques?
Pro's: results are generalizable to population
Con's: More time and resource intensive + you need a good sampling frame, most of the time not direct available.
Nonprobability sampling: the elements of the population do not have a known chance of being selected as a subject.
Pro's: less time and resource intensive
Con's: results are not generalizable to population.
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