Chapter 10: Hypothesis Testing & Type I and Type II Errors. Flashcards

1
Q

What letter and number do we use for a null hypothesis?

A

H0.

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2
Q

What letter and number do we use for an alternative hypothesis?

A

H1.

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3
Q

What are the hypotheses we use for a 1-tail hypothesis test?

A

H0: λ = a.
H1: λ </> a.

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4
Q

What are the hypotheses we use for a 2-tail hypothesis test?

A

H0: λ = a.
H1: λ a.

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5
Q

What do we do to the significance level for a 1-tail test?

A

Nothing. (e.g. 10% = 0.1).

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6
Q

What do we do to the significance level for a 2-tail test?

A

We half it. (e.g. 10% = 0.1/2 = 0.05).

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7
Q

What happens to X~Po(λ) when we have a sample size?

A

We must multiply the value of λ by the sample size. (e.g. in a sample size of 5, X~Po(λ) –> X~Po(5λ).

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8
Q

After finding xInvP, what do we have to do to each value given in the warning?

A

Check them in Pcd with Lower 0 and the values given as the upper, with lambda the same to give us p-values.

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9
Q

How do we know which critical value to choose?

A

We choose the critical value which gives us a p-value that lies inside the critical region (it is lower than the significance level).

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10
Q

How do we work out the test statistic?

A

By multiplying the average rate by our sample size.

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11
Q

Do we Accept or Reject H0 if our Test Statistic is inside the critical region?

A

Reject H0.

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12
Q

Do we Accept or Reject H0 if our Test Statistic is outside the critical region?

A

Accept H0.

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13
Q

What saying is there to remember whether or not to Accept/Reject H0?

A

“If the probability is low, reject H0 (zero).”

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14
Q

What is the conclusion if we Accept H0?

A

“There is insufficient evidence to suggest that…”

(Opposite of what you would think).

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15
Q

What is the conclusion if we Reject H0?

A

“There is sufficient evidence to suggest that…”

(Opposite of what you would think).

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16
Q

What does a Type I Error mean?

A

We rejected the null hypothesis (H0), when it was actaully true.

17
Q

What’s another name for a Type I Error?

A

False Positive.

18
Q

What does a Type II Error mean?

A

We accepted the null hypothesis (H0), when it was actually false.

19
Q

What’s another name for a Type II Error?

A

False Negative.

20
Q

How do we calculate a Type I Error?

A

P(Type I Error) = Probability X is greater to and equal or less than and equal to the critical value.