Distributions and Probability

Question 1

What is a normal distribution/symmetrical skew?

Answer 1

-When data is symmetrical around central scores e.g. mean, median and mode are equal

Question 2

What is a positive skew?

Answer 2

-Tails out to the right and leans to the left
-Mode - Median - Mean (left to right)

Question 3

What is a negative skew?

Answer 3

-Tails out to the left and leans to the right
-Mean - Median - Mode (left to right)

Question 4

How to calculate the skew?

Answer 4

Skew = 3(mean-median)
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Standard deviation

-If the skew is <0, the data is negatively skewed
-If the skew is >0, the data is positively skewed
-CHECK ON GOOGLE DOCS

Question 5

What is a parametric test?

Answer 5

-Assumes that values such as the mean and standard deviation accurately reflect the population distribution

Question 6

Why do we transform data into Z scores?

Answer 6

-This can help to standardise the data and reduce the impact of skewness
-This tells us exactly how many standard deviations someone was from the mean:
-68% of the population are within a z score of ±1
-95% of the population are within a z score of ±1.96 (round up to 2)
-99.7% of the population are within a z score of ±2.96 (round up to 3)

Question 7

What is the equation of calculating the Z score?

Answer 7

Z = Individual point - Group mean
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Standard deviation

Question 8

What are the pros and cons of using distributions?

Answer 8

-(+) Can transform data to a standardised scale
-(+) Scale adheres to normal distribution
-(+) Can compare things relative to their own population
-(+) Use the entire dataset
-(-) Sampling errors can occur (how representative they are of the population)
-(-) Standard errors can occur (SEM = standard deviation ÷ square root of num of datapoint)
-(-) Confidence intervals (range of values that contain the true value of statistic e.g. mean)