S3 Flashcards

1
Q

How do you find Sxx from a list of numbers

A

Square all of them add together. Then subtract the mean squared multiplied by the number of numbers.

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2
Q

What does PDF stand for?

A

Probability density function

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3
Q

How would you show that a statement is constant with f(x) being a PDF?

A

Integrate between the range and it will be 1

Negative probabilities won’t occur

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4
Q

How do you find the mean of a continuous random variable from the PDF?

A

∫xf(x) between the given limits. This is expectation of x

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5
Q

How do you find the variance of a continuous random variable from the PDF?

A

∫x²f(x) between the limits
Subtract E(x)²
Var(X)= E(X²)-E(X)² State this explicitly.

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6
Q

If you found the mean and variance of a random variable X, what would the mean and variance of Y be if Y=4X-1

A

Multiply the mean by 4 and subtract 1

Multiply variance by 4²

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7
Q

How do you find the probability of a random variable being between two limits when given a PDF

A

Intergrate between the two limits.

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8
Q

How is mode found with a PDF?

A

It is the highest point.

Differentiate to find it.

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9
Q

How is the median found from a PDF?

A

The integral between m and one of the limits is 0.5

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10
Q

What is a uniform distribution?

How is mean and variance found?

A

Looks rectangular when drawn
Mean is (a+b)/2
Variance = (1/12)(b-a)²

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11
Q

If given a PDF of f(x), how would you find the CDF?

A

The CDF a F(x) is the integral of the PDF between 0 and x

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12
Q

What so you have to say when writing down a PDF?

A

F(x) =………..
Give the limits of the function
Say that it is 0 otherwiise

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13
Q

What do you assume when doing a chi squared test?

A

Observed frequencies are approximately normally distributed about the expected frequencies.

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14
Q

When are groups put together with chi ² tests?

A

To make sure all groups have expected frequencies greater than 5

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15
Q

How are the degrees of freedom found with chi² squared test?

A

= no. of classes - no. of estimated parameters -1

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16
Q

What is equal to what with a 🐠 distribution ?

A

Mean and variance

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17
Q

What is assumed for a 🐠 distribution ?

A

Events take place randomly, independently and at a constant overall mean rate.

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18
Q

What do you assume for a binomial distribution

A

Events are random and independent.

The mean is np

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19
Q

What are confidence intervals a measure of?

A

In repeated sampling

90% of intervals generated in this way would contain the true population mean.

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20
Q

How are confidence limits found?

A

Sample mean ± K*(σ÷√(size of sample))

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21
Q

What is the difference between s and σ

A

S is the sample SD
σ is the population SD
When finding confidence limits you often have to approximate ⍬ with S.
When n≥50 it is a good aproximation.

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22
Q

What is the standard error of the mean?

A

The standard deviation of the sample means is σ÷√n

23
Q

What does the central limit theorem say?

A

For a sample of size n drawn from a distribution with mean μ & variance σ² the distribution of the sample mean is approximately
N(μ,(σ²÷n)) for sufficiently large values of n.(25+)

24
Q

When do you use 1.645, 1.96, and 2,576 values of K?

A

When you already know the parent population SD σ
If you estimate σ from the sample, you use the t distribution and not the normal provided the parent population is normally distributed. Thus you use the values of k further up the table.

25
Q

If you had a large sample and you wanted to produce confidence intervals but had to estimate the parent population SD (σ) what values of K would you use?

A

If n is large enough (50+) then confidence intervals worked out using the normal distribution will be accurate enough and you can use the values of k at the bottom of the table.

26
Q

When conducting a t test with paired data, what is done with significance levels?

A

When looking for the critical value in the table, look in the column with double the significance level given in the question. If it is a two tailed test, just use the given level.
This is because the tables are made to give each tail a probability of 0.5p%

27
Q

Assumptions for wilcoxen test

A

The data is symmetrically distributed about the mean/median

28
Q

When conducting a Wilcoxen test, what is done with any data that is equal to the median?

A

Removed from sample.

29
Q

What are W₊ and W₋?

A

W₊ sum of the ranks above the median.

W₋ sum of the ranks below the median.

30
Q

How do you check W₋ and W₊ are correct?

A

W₋+W₊ = 0.5n(n+1)

31
Q

When conducting a Wilcoxen test when is W+ and W- used?

A

If two tailed the smaller of W- and W+

If one tail test and you are testing if the true median is less than the believed median, use W+

32
Q

Where are the critical values found for the Wilcoxen test?

A

Page 30 of the formula booklet.

33
Q

For the Wilcoxen test, how do you compare W and the critical value?

A

If W is less than or equal to critical value, reject H0 and accept H1

34
Q

When do you use the normal distribution?

A

When the sample is large

When the sample is small, the distribution is normal and the population variance is known.

35
Q

When do you use the Wilcoxen test?

A

When a sample is small and nothing is known about the distribution of the background population.

36
Q

When do you use the t-distribution ?

A

The sample is small, the distribution is normal and the population variance isn’t known.

37
Q

What is opportunity sampling?

A

Sampling which selects from those that are (easily) available

38
Q

If a PDF is f(x)=x/50 for 0 to 10, how would you find E(3x+4)?

A

Multiply (3x+4) by x/50 for 1/50*(3x² +4x) and integrate between limits.

39
Q

How would you find E(x²)

A

Multiply the PDF by x² and intergrate between range

40
Q

What is subtracted from what with a Wilcoxen test?

A

Values - median being tested

41
Q

If when doing a Wilcoxen test and the critical value is equal to the W value, what do you do?

A

Significant. Accept H1

42
Q

Why is paired data appropriate on occasion?

A

To remove differences between groups, people, authorities

43
Q

What is the significance level?

A

The significance level, also denoted as alpha or α, is the probability of rejecting the null hypothesis when it is true. For example, a significance level of 0.05 indicates a 5% risk of concluding that a difference exists when there is no actual differe

44
Q

If the mean duration of an event can be normally distributed with ( μ,σ^2), what distribution would give the mean time for three events to occur?

A

It would be Normally distributed and the mean would be the same.
Variance of total time is 3σ^2, but when you have to divide by 9 to get the variance for the mean.
You divide by 9 and not 3 as 9=3^2 and you have to square constants when multiplying by a variance.

45
Q

Give two reasons why an investigator might need to take a sample in order to obtain information about a population.

A

For example, need to take a sample because the population might be too large for it to be sensible to take a complete census.
Because the sampling process might be destructive

46
Q

State two requirements of a sample.

A

Sample should be unbiased
Sample should be representative (of the population)
data should not be distorted by the act of sampling;
data should be relevant.

47
Q

Discuss briefly the advantage of the sampling being random.

A

A random sample … enables proper statistical inference to be undertaken …… because we know the probability basis on which it has been selected

48
Q

How is the median found from a CDF?

A

solve the equation F(m) = 0.5

49
Q

In what form is a confidence interval given?

A

If you found it was 99 to 101 you would write it (99,101)

50
Q

What do you assume when using a t test?

A

The sample is taken from a normally distributed population.

51
Q

How would you conduct a cluster sample?

A

Identify clusters which are capable of representing the population as a whole
Choose a random sample of clusters
Randomly sample within the chosen clusters.

52
Q

What is a simple random sample?

A

A simple random sample is one where every sample of the required size has an equal chance of being chosen.

53
Q

Why might you conduct a cluster sample over a simple random sample ?

A

If you were investigating school chlidren, simple random would mean talking to a few pupils at lots of different schools which is more work than making a few schools clusters and sampling them.

54
Q

What is stratified sampling and why might you do it?

A

There are identifiable subgroups or strata that might exhibit different characteristics.
Each stratum is randomly sampled.
Use it to obtain a representative sample.
Can get information on the individual strata.