Biostatistics | Midterm - HYPOTHESIS TESTING

Question 1

A statement about one or more populations.

• It is usually concerned with the parameters of the population. e.g. the hospital administrator may want to test the hypothesis that the average length of stay of patients admitted to the hospital is 5 days

Answer 1

HYPOTHESIS TESTING

Question 2

a statement of the research question that sets forth the appropriate statistical evaluation

Answer 2

Hypothesis

Question 3

statement of no differences or association between variables

Answer 3

Null hypothesis “H0”

Question 4

statement of differences or association between variables

Answer 4

Alternative hypothesis “H1”

Question 5

STEPS IN HYPOTHESIS TESTING

Answer 5

1. Make a prediction
2. Decide on a statistical test to use
3. Select a significance level and a critical region (region of rejection of the null hypothesis). To do this you must consider two things.
   
   • Whether both ends (tails) of the distribution should be included.
   • How the critical region of a certain size will contribute to Type I or Type II errors.
4. Computing the test statistic - The test statistic is not a mean, sd or any form of descriptive data. It is simply a number that can be compared with a set of results predicted by the sampling distribution.
5. Compare the test statistic to the sampling distribution (table) and make a decision about the null hypothesis reject it if the statistic falls in the region of rejection
6. Consider the power of the test – its probability of detecting a significant difference – parametric tests are more powerful

Question 6

Testing a Hypothesis:
outcome is expected in a single direction (e.g., administration of experimental drug will result in a decrease in systolic BP)

Answer 6

One-tailed hypothesis

Question 7

Testing a Hypothesis:
the direction of the effect is unknown (e.g., experimental therapy will result in a different response rate than that of current standard of care)

Answer 7

Two-tailed hypothesis

Question 8

Statistical Errors:
False Positive

Answer 8

Type 1

Question 9

Statistical Errors
False Negative

Answer 9

Type 2

Question 10

Under the assumption that H0 is correct, probability that the observed test statistic is skewed towards H1

Answer 10

Probability Value (p-value

Question 11

Confidence Intervals:
90%

Answer 11

p<1.0 (0.5 for two-tailed)

Question 12

Confidence Intervals:
95%

Answer 12

p<0.05

Question 13

Values:
the set cut-off value from statistical table (e.g. t-test 1.96 = 95% CI; z-test 2.58 for two tailed

Answer 13

Critical

Question 13

Confidence Intervals:
99%

Answer 13

p<0.01

Question 14

Test to use for Analysis of Continuous Data

Answer 14

Correlation t-test, T-test

Question 15

Values:
the value from the data collected

Answer 15

Computed

Question 16

Test to use for Analysis of Categorical Data

Answer 16

Chi-square, Logistic regression

Question 17

Types of DATA ANALYSIS

Answer 17

Analysis of Categorical Data
Analysis of Continuous Data

Question 18

Measures of Association

Answer 18

PARAMETRIC & NON-PARAMETRIC

Question 19

PARAMETRIC

Answer 19

Normality
Skewness/ kurtosis
Linearity
Heteroscedasticity/ homoscedasticity

Question 20

Correlation / Test of Relationship
- Parametric Test

Answer 20

Pearson r

Question 21

Correlation / Test of Relationship
- Non-parametric

Answer 21

spearman-rho

Question 22

Correlation / Test of Relationship
1.Tests

Answer 22

a. Parametric - pearson-r
b. Non-parametric – spearman-rho
c.Chi-square
Note: if data is encoded as frequency – indicate data weights
d. Kendall-Q for nominal data
e. Phi-coefficient – ordinal data

Question 23

Measure of relationship

Answer 23

a. Direct
b. Indirect

Question 24

Strength of relationship

Answer 24

a. -1 to +1; 0 = no correlation
b. Scatter plot

Question 25

Interpreting strength of correlations:
0 – 0.25

Answer 25

Little or no relationship

Question 26

Interpreting strength of correlations:
0.25 – 0.50

Answer 26

Fair degree of relationship

Question 26

Interpreting strength of correlations:
0.50 - 0.75

Answer 26

Moderate degree of relationship

Question 26

Interpreting strength of correlations:
0.75 – 1.0

Answer 26

Strong relationship

Question 27

Interpreting strength of correlations:
1.0

Answer 27

perfect correlation

Question 28

• concerned with the effect of one variable to the relationship of 2 variables
• Relationship of two variables while holding the third variable constant. (eg. Science and Reading while holding IQ constant)

Answer 28

Partial Correlation

Question 29

Test of Difference:
>30 samples; large sample size
T-test = <30 samples (homogenous) – tested by Levene’s test of homogeneity; hypothesis = sample is not homogenous

Answer 29

Z-test

Question 30

Test of Difference:
<30 samples (homogenous) – tested by Levene’s test of homogeneity; hypothesis = sample is not homogenous

Answer 30

T-test