Randomly collected samples with sufficient data points from population distributions are normally distributed; that is, they follow a bell curve. Learn some basic rules of thumb that help understand a normal distribution.
- [Instructor] You've got your sample, and you've…run some stats and you've retrieved the sample mean.…Now, how confident are you that this statistic…represents the actual population parameter?…Sure, you've randomly sampled.…Sure, you have a large sample size,…but is that enough?…Well, even if you're not super-confident,…we can use a normal distribution to help us create…a range around the sample mean that's very likely to contain…the true population parameter.…Let's take a look at this normal distribution.…
The properties of a normal distribution allow us…to determine how confident we can be in our estimate.…The normal distribution is essentially…a probability distribution.…The center-most point is the mean,…the X-axis is the variable,…and the Y-axis is the frequency distribution.…The total area under a curve is equal to 100%.…If we were to imagine women's heights…from our sample being plotted on here as a histogram,…the majority of the heights would be…in the middle of the distribution.…
Let's make some assumptions about our data set.…
- Quantitative vs. qualitative analysis
- Sample size considerations
- Normal distribution
- Estimating the population mean
- One-sample t-test
- Paired-sample t-test
- One-way and two-way ANOVA
- Repeated measure ANOVA
Skill Level Beginner
1. General Notions about Science and Research
2. Quantitative Research Fundamentals
3. One-Sample T-Test
4. Paired-Samples T-Test
5. Balanced One-Way ANOVA
6. Two-Way ANOVA
7. Repeated Measures ANOVA
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