Question

c. mode:
d. percentile rank:
e. range:
f. standard deviation:

1. draw and explain the difference between normal and skewed distribution (negative & positive).
2. what are inferential statistics?
3. when is it appropriate to apply findings to a population?

a.
b.
c.
i. meta - analysis:

1. what does it mean for results to be statistically significant?
2. what is effect size?

Explanation:

1. A normal distribution is symmetric, bell - shaped with mean = median = mode. A skewed distribution is asymmetric. In a positively skewed distribution, the tail is on the right side and mean > median > mode. In a negatively skewed distribution, the tail is on the left side and mean < median < mode.
2. Inferential statistics are used to make inferences, predictions, or generalizations about a population based on a sample of data. This includes hypothesis testing, confidence intervals etc.
3. It is appropriate to apply findings to a population when the sample is representative (randomly selected and large enough to capture the population's characteristics), the study design is valid, and there are no significant biases in sampling or data collection.
4. Statistically significant results mean that the observed results are unlikely to have occurred by chance under the null hypothesis. Usually, a p - value (probability value) less than a pre - specified significance level (e.g., 0.05) indicates statistical significance.
5. Effect size is a measure of the magnitude of the relationship or difference between groups in a study. It provides information beyond statistical significance about how large or important the effect is in practical terms.

Answer:

1. A normal distribution is symmetric and bell - shaped with mean = median = mode. Skewed distributions are asymmetric (positive: tail on right, mean > median > mode; negative: tail on left, mean < median < mode).
2. Inferential statistics make inferences, predictions or generalizations about a population based on sample data.
3. When the sample is representative, study design is valid and there are no significant biases.
4. Observed results are unlikely to have occurred by chance under the null hypothesis (usually p - value < 0.05).
5. A measure of the magnitude of the relationship or difference between groups in a study.