Statistics 1

Question 1

What is the definition of a population?

Answer 1

Every member with selected characteristics and sharing common property in a specific region

Question 2

What is the definition of a sample?

Answer 2

A representative sub-set of a given population, unrelated and chosen at random

Question 3

What is the difference between the response (dependent) variable and the explanatory (independent) variable?

Answer 3

The response (dependent variable is of interest in an experiment, it depends on another factor (independent/explanatory) variable to cause change.

Question 4

What are the two sub-sets of qualitative data?

Answer 4

Nominal Data - categorical information that lacks inherent order or ranking

Ordinal Data - information with order or ranking, differences between values are not quantifiable e.g. survey responses or educational levels

Question 5

What are the two sub-sets of quantitative data?

Answer 5

Discontinuous - obtained by counting integers

Continuous - (Most used) obtained by measurement e.g. height, BMI

Question 6

What type of data is:
Number of carbon atoms in a molecule

Answer 6

Discontinuous quantitative

Question 7

What type of data is:
Mass of a chemical compound weighed on a balance

Answer 7

Continuous quantitative

Question 8

What type of data is:
Absorbance measured using a spectrophotometer

Answer 8

Continuous quantitative

Question 9

What type of data is:
Gender of students in a class

Answer 9

Nominal Qualitative

Question 10

What type of data is:
Educational levels of students in a class

Answer 10

Ordinal Qualitative

Question 11

Define Accuracy

Answer 11

Closeness of measurements to the true value

Question 12

Define precision

Answer 12

Closeness of repeated measurements to eachother

Question 13

Define Data Set

Answer 13

Collection of information based on an experiment or research question, collected in term of observations and variables, ready to be processed, analyzed, distributed or shared.

Question 14

Define descriptive statistics

Answer 14

Summarize a set of data values in terms of center and spread

Question 15

What does average show?

Answer 15

The general tendency of the data

Question 16

What distribution of data can you find the true mean?

Answer 16

Normally distributed data

Question 17

Define variance

Answer 17

Average squared deviation from the mean

Question 18

Define Standard Deviation

Answer 18

Variability or spread of the data from the mean of the sample

Question 19

Define Standard Error

Answer 19

Deviation from the mean of the populations, this tends to be estimations used to calculate confidence

Question 20

What is the Confidence Interval?

Answer 20

What percentage confidence you are that if someone repeated the test with a different sample, you would get the same results

Question 21

Give the basic principles of coefficient of variance (CoV)

Answer 21

• Larger the number the larger the spread
• Normally expressed as a percentage of the mean
• Useful for comparisons of 2 data sets in different units

Question 22

Give the formula for Coefficient of variance (CoV)

Answer 22

CoV = (SD/mean)*100

Question 23

Define H0

Answer 23

The null hypothesis - there is no correlation/ difference/ association

Question 24

Define H1

Answer 24

Quantitative or alternative hypothesis
there is a correlation
H1 and H0 are mutually exclusive

Question 25

What is the P value

Answer 25

The probability (chance) that the null hypothesis is true with 95% confidence. 0.05 (5%) is the statistical cut off of rejection of the H0.

Question 26

What is the true cutoff for the P value?

Answer 26

0.05/number of predictor variables

Question 27

Why is it best t under go 2-tailed tests rater than on-sided

Answer 27

A hypothesis can either be one sided or 2 sided and you can test for statistical significance in both directions. If you only test in one direction you may miss an effect in the other direction!

Question 28

What is the odds ratio?

Answer 28

A value indicating the strength of the relationship between 2 variables in data. Compared the relative odds of the occurance of the outcome of interest (cancer vs no cancer), given the exposure to the variable of interest (age)

Question 29

What does Odds Ratio mean in relationship to 1

Answer 29

- OR = 1 variable does not effect the odds of the outcome - OR > 1 variable associated with higher odds of an outcome (Increase the risk of the response variable) - OR < 1 variable associated with lower odds of an outcome (Decrease the risk of the response variable)

Question 30

What is the Z score ?

Answer 30

Odds ratio / standard error of the odds ratio

Question 31

What are statistics tests used for?

Answer 31

To test the probability that the null hypothesis is true

Question 32

When would you use z-test?

Answer 32

When the sample size is small (n<30) and/or the population variance is known

Question 33

When would you use t-test?

Answer 33

When the sample size is small (n<30) and/or the population variance is unknown

Question 34

When would you use Chi-squared?

Answer 34

Goodness of fit - examine whether the observed results are in order with the expected values (categorical data)

Question 35

When would you use Fisher Exact?

Answer 35

Goodness of fit - gauge if there is a significant difference between proportions of the categories in two group variables

Question 36

When would you use F-test?

Answer 36

Compare variances of 2 samples or the ratio of variances between multiple groups

Question 37

When would you use ANOVA?

Answer 37

Uses F-tests to statistically test the equality of means on 3 or multiple groups of quantitaive variables

Question 38

When would you use Wilcoxon Rang

Answer 38

Test the equality of means on 3 or multiple groups - used when data is not normally distributed

Question 39

What does the result of a t- statistic mean?

Answer 39

The higher the value, the lower the chance that the two samples means are from the same population The higher the value of t the more likely that the two samples means are to be different.

Question 40

What is a Type I error?

Answer 40

False positive Occurs if you reject the H0 while you are supposed to accept it due to data bias

Question 41

What is a Type II error?

Answer 41

False negative Occurs when you accept the null hypothesis when you were supposed to reject it due to a lack of power