Samples and Central Limit Theorem

Question 1

What are sample means?

Answer 1

Sample means are the means of different samples
With a reasonable number of sample means the means will approximately equal the population mean
Closer to the mean there should me more samples

Question 2

Outline the distribution of sample means

Answer 2

Sample means form a normal distribution
Looks similar to the normal distribution for individuals within a group but its different as each sample has a mix of scores so highs are cancelled out by low
The SD of sample means around the mean of the sample means is smaller than the SD of the actual scores around the population mean
Less variability in distribution

Question 3

What is standard error?

Answer 3

SE= SD/ square root of n

SD= Standard deviation
N = number in sample

1 Z score = 1 SE

Question 4

How do we calculate how many SEs will a certain percentage of the sample lie within?

Answer 4

Divide by 2
Divide by 100
Then find this value on the normal table

Question 5

What is the null hypothesis?

Answer 5

No significant difference between a hypothesised value of a population parameter and its value estimated from a sample of the population

Question 6

When do we reject the null hypothesis?

Answer 6

We set ourselves a threshold - 5 and 1 % are common
If the mean is in the rarest threshold then we conclude that the null hypothesis is not true
We accept the alternate hypothesis (H1)
With an individual the Z score needs to be of a probability of 0.4750 or above to accept H0