Normal distribution

Question 1

what are 2 examples of normal distributions

Answer 1

Question 2

what is the equation for normal distribution in the real world (non-standardised)

Answer 2

Question 3

what is the equation for hypothesis testing in stats land (standardised)

Answer 3

Question 4

How do we get from real world hypothesis testing (non-standardised) to stats land (standardised)

Answer 4

Question 5

How to calculate probabilities steps

Answer 5

Question 6

how to calculate the probability for a question like this using standardised hypothesis testing

Answer 6

steps:
1) draw the bell curve
2) put your mean and variation in using 0 and 1
3) depending on the sign as it is greater than put -0.28 as the lower and 99999 us the upper
4) the answer is also equals to the area in which you can now label on the bell curve

Question 7

how to calculate ‘z’ values using standard normal distribution

Answer 7

Question 8

how to calculate the ‘z’ value for a question like this using standardised normal distribution

Answer 8

steps:
1) draw the bell curve and label the area
2) use N(INV) function and have mean and variation as 0 and 1
3) the area is the probability given in the question
4) the tail depends on whether it is greater than or less than, for this question right tailed because it is greater than (wherever the arrow points it is the tail)

this is the same method to use with given values of the normal such as a given value of the mean and sigma just sub them in instead of 0,1

Question 9

how to calculate the probability with given normal distribution (non-standard)

Answer 9

steps:
1) draw the bell curve
2) use Ncd, and have the mean be the mean and sigma as the sigma (in this example mean = 40, sigma = the square root so 3
3) do the upper or lower, in this example lower is -99999 and upper is 45
4) draw it in the bell curve

Question 10

how to solve a converting out of a given normal distribution to a standard normal distribution

Answer 10

steps:
1) sub in the values of the given normal distribution into the z formula
2) then find the probability using mean and sigma as 0,1 and the value your testing with as the result of the z formula
3) to decide which way to test it is the same as the distribution you used to convert to standard, in this example it is greater than 15

Question 11

what is the formula used to convert and connects standard normal and non-standard normal distribution (Z formula)

Answer 11

Question 12

how to solve a converting out of a standard normal distribution to a given one

Question 13

how to calculate the probability when we don’t know a by converting into standard normal from given normal distribution

Answer 13

steps:
1) use NInv with the area and the standard normal mean and sigma
> in this example NInv ( 0.4, 1, 0)
2) sub in the values into the Z formula with the unknown being x
3) set it equal to the value obtained from the NInv
4) solve for x

Question 14

how to find the missing value of the mean or sigma

Answer 14

steps:
1) use NInv(area,1,0)
2) sub all the values you can into the z formula
3) set this equal to the NInv value
4) then solve for whatever the missing value is

Question 15

How to calculate the mean values from a sample

Answer 15

steps:
1) write out your given normal distribution
2) then write out your normal distribution with the sample mean
3) this will have your mean be the same and your sigma be your (original sigma/square root of the sample mean) ^2
4) your standard deviation = is just your sigma not squared
5) put it in Ncd with the correct values and thats your answer

Question 16

How to solve a hypothesis on a mean value from a sample

Answer 16

steps:
1) define what T or X is
2) write the normal distribution with the given values
3) write the sample mean normal distribution and state sd
4) write your h0 and h1 using mean = …
5) test the hypothesis using your mean sample normal distribution
6) if it is less than the critical region reject h0 and conclude

Question 17

how to tell if a hypothesis test is one or two-tailed

Answer 17

ask hannah

Question 18

what are the 2 assumptions needed to have to use the normal to approximate the binomial

Answer 18

Question 19

how do we approximate from binomial to a normal distribution

Answer 19

using

Question 20

what is one thing we have to do due to going from continuous data to discrete data when approximating a binomial to a normal

Answer 20

Question 21

Answer 21

Question 22

How to solve an approximating binomial to normal question

Answer 22

steps:
1) write down the binomial distribution
2) convert into normal distribution (np, np(1-p))
3) find what you are testing for and continuity correct
4) plug it all in and answer