Inferential Stastics - Chapter 1

Question 1

What is the Central Limit Theorem (CLT)?

Answer 1

No matter what the shape of the original data is — whether it’s weird, skewed, or lopsided — if you take many random samples of that data and calculate the average of each sample, those averages will form a normal (bell-shaped) distribution, as long as the sample size is big enough.

Question 2

What is sampling distribution?

Answer 2

A sampling distribution is the distribution (spread/shape) of a statistic (like the mean or median) based on many samples taken from the same population.

Question 3

What are the steps of Hypothesis testing?

Answer 3

Formulating a null hypothesis ( H 0 ) and an alternative hypothesis (H 1
2.
Select the level of significance
3.
Using the data calculate a test statistic
4.
Calculate critical value
5.
Compare the test statistic to a critical value (table value)
6.
Determine whether to accept or reject H 0

Question 4

When do you Reject H0?

Answer 4

Calculated value (test statistic) > Table value (critical value)

Question 5

When the confidence level is 90%, 95% and 99% what is the l.o.s?

Answer 5

l.o.s α=10% = 0.1
l.o.s α=5% = 0.05
l.o.s α=1% = 0.01

Question 6

What are the two types of errors?

Answer 6

Type I error :
A Type I error occurs when we reject the null hypothesis H0 when it is actually true.
Type II error:
A Type II error occurs when we fail to reject the null hypothesis H0H_0H0 when it is actually false.