Y2 Stats

Question 1

What does the PMCC describe?

Answer 1

The linear correlation between 2 variables, from -1 to 1.

Question 2

What does y = ax^n equal in log form?

Answer 2

log y = log a + n log x

Question 3

What does y = kb^x equal in log form?

Answer 3

log y = log k + x log b

Question 4

What do you do for exponential modelling questions?

Answer 4

Sub between x / y and whatever they’re coded to as needed

Question 5

What is PMCC represented by?

Answer 5

Letter r for a set of data

Question 6

What does PMCC +- 1 represent?

Answer 6

All the points lying on a straight line

Question 7

What does A U B mean?

Answer 7

Event A or event B. So union of them.

Question 8

What does A intersection B represent?

Answer 8

A and B, overlap of them/

Question 9

What does P(A|B) mean?

Answer 9

Probability of A happening given that B has already occurred.

Question 10

What happens if P(A|B) = P(A)?

Answer 10

Then events A and B are independent.

Question 11

How much data is within 1 standard deviation of the mean for a normal dist?

Answer 11

68%

Question 12

How much data is within 2 standard deviations of the mean for a normal dist?

Answer 12

95%

Question 13

How much data is within 3 standard deviations of the mean for a normal dist?

Answer 13

Around 99.7%

Question 14

What does the standard normal dist. have?

Answer 14

Mean 0, standard deviation 1.

Question 15

What is the standard normal dist. written as?

Answer 15

Z ~ N(0,1^2)

Question 16

How do you code normal distributions to the standard normal dist?
In form X ~ N(u, var^2)

Answer 16

Z = (X - u) / var.
Allows you to find amount of standard deviations away from the mean. Could also just use InvN.

Question 17

How do you approximate a binomial dist to a normal one?

Answer 17

u = np (duh)
var = root(np(1-p))

Question 18

How do continuity corrections work?

Answer 18

You should only include values that will ROUND to the binomial’s bound. Pay attention to less than or less than / equal to.

Question 19

What is the sample mean for a sample size n distributed along X ~ N(u, var^2)?

Answer 19

Xbar ~ N(u, (var^2)/n). So just divide var^2 by n.

Question 20

How do you standardise the coding to a sample mean? So coding
Xbar ~ N(u, var^2/n).

Answer 20

Z = (Xbar - u) / (var/root(n))