10. MTB Step 3 - Null Hypothesis, the Meaning of P-Value, Error, Power, Extra Definitions)

Question 1

HYPOTHESIS

What is the meaning of Null Hypothesis?

Answer 1

Null Hypothesis (H₀) = No Difference/No Change/No Benefit

Question 2

HYPOTHESIS

What is the meaning of Alternate Hypothesis (H₁)?

Answer 2

Alternate Hypothesis (H₁) = Difference/Change/Benefit

Question 3

HYPOTHESIS

1. What does it mean to ACCEPT the Null Hypothesis (H₀)?
2. What does it mean to ACCEPT the Alternate Hypothesis (H₁)?

Answer 3

1. It means ACCEPTING the hypothesis that there is No Difference/No Change between groups (Accept H₀).
2. It means ACCEPTING the hypothesis that there is a Difference/Change between groups (Accept H₁).

Question 4

HYPOTHESIS

1. What does it mean to REJECT the Null Hypothesis (H₀)?
2. What does it mean to REJECT the Alternate Hypothesis (H₁)?

Answer 4

1. It means REJECTING the hypothesis that there is No Difference/No Change between groups (Accept H₀).
2. It means REJECTING the hypothesis that there is a Difference/Change between groups (Accept H₁).

Question 5

P - VALUE

What is the meaning of P-Value?

Answer 5

P-Value = the Probability of the Hypothesis being True or Not True.

Question 6

P - VALUE

What does it mean if you have a P-Value of 0.05?

Answer 6

P-Value of 0.05 means there is a 95% chance that the Alternate Hypothesis (H₁) is True:

• a 95% chance that, if the test were repeated, it would reproduce the current findings;
• same results could be replicated 95% of the time.

Means there is still a 1 in 20 chance that the data is random

Question 7

TYPE I ERROR

What is the meaning of a Type I Error (alpha error)?

Answer 7

• A False Positive (FP) result
• Rejecting the Null Hypothesis when it really is True
• Saying the treatment works when it really doesn’t
• Accepting the Alternate Hypothesis when it isn’t really true
• Saying there is a Statistically Significant difference in the data when there really isn’t

Question 8

TYPE I ERROR

What is the Rate of a Type I error (Alpha error) related to?

Answer 8

The Significance level of a test.

Question 9

TYPE I ERROR

What INCREASES the Probability of a Type I error?

Answer 9

A higher Alpha increases the probability of a Type I error (α).

α = 0.05

The highest α you should use for significance cutoff is α = 0.05

An α of 0.05 indicates that you are willing to accept a 5% chance that you are wrong when you reject the null hypothesis.

Question 10

TYPE II ERROR

What is the meaning of a Type II Error (beta error)?

Answer 10

• A False Negative (FN) result
• Accepting the Null Hypothesis when it really is False
• Saying the treatment doesn’t work when it really Does
• Rejecting the Alternate Hypothesis when it really is true
• Saying there is no Statistically Significant difference in the data when there really is

Question 11

TYPE II ERROR

What is the Probability of a Type II Error (denoted as ß) related to?

Answer 11

The Power of a study.

Question 12

TYPE II ERROR

What DECREASES the Probability of a Type II Error (ß)?

Answer 12

A higher Alpha decreases the Probability of a Type II error (ß)?

Question 13

POWER

How is Power calculated?

Answer 13

Power = 1 - ß

Question 14

POWER

What INCREASES the Power of a study?

Answer 14

Larger sample sizes increase the Power of a study.

Question 15

POWER

What DECREASES the Power of a study??

Answer 15

Smaller sample sizes decrease the Power.

Question 16

DEFINITION

What is Selection Bias?

Answer 16

The Inappropriate Selection or Poor Retention of study participants.

Question 17

DEFINITION

What is Outcome Misclassification?

Answer 17

An error that occurs in epidemiologic studies when the outcome of interest is misclassified.

Question 18

DEFINITION

What is Early Termination of a study?

Answer 18

Occurs when a study shows an overwhelmingly positive or negative effect before the study’s planned conclusion.