Lecture 3: Starting Points in Data Analysis

Question 1

What are the quartiles on a boxplot?

Answer 1

first quartile (Q1): divides the lowest 25% of the data form the highest 75% (25th percentile or lower quartile)

second quartile (Q2): divides the data in half. 50th percentile or median

third quartile (Q3): divides the highest 25% of the data form the lowest 75%. 75th percentile or upper quartile

Question 2

What is the interquartile range (IQR)?

Answer 2

Q3-Q1
sometimes referred to as a middle 50%
measure of variability
median and IQR often reported for variables that are not normally distributed

Question 3

What are outliers?

Answer 3

extreme observations in your variable of interest

Question 4

How does SPSS identify outliers?

Answer 4

according to Tukey’s fences method

• values below Q1-(1.5IQR) or above Q3+(1.5IQR) –> these are marked with an O
• values below Q1-(3IQR) or above Q3+(3IQR) –> these are marked with an * (more extreme values)

Question 5

Quantile-Quantile Plots (Q-Q Plots)

Answer 5

determines if a variable comes form a specified distribution

Question 6

Stem and leaf plot

Answer 6

displays the frequency at which certain classes of values appear in the data
can be used to examine distribution of data as well as extreme values

Question 7

What are the statistical tests for normality?

Answer 7

Shapiro-Wilk test

KS test

Question 8

What is the Shapiro-Wilk test?

Answer 8

tests null hypothesis that data came from a normally distributed population
more accurate when the sample sizes are <2000

Question 9

What is Kolmogorov-Smirnov test?

Answer 9

Goodness of fit test –> tests null hypothesis that a sample comes from a specified distribution
More accurate when sample sizes are large (n ≥ 2000)

Question 10

What does it mean when you reject the null hypothesis in the test for normality?

Answer 10

It means that you fail the normality test and have a significant p value (<0.05) so you dont have data that came from a normally distributed population

Question 11

What does it mean when you accept the null hypothesis or fail to reject it in the test for normality?

Answer 11

It means that you pass the normality test and have a non-significant p-value (>0.05) so you have data that comes from a normally distributed population.

Question 12

What are some other parameters to assess normality?

Answer 12

Skewness and Kurtosis

Question 13

What is skewness?

Answer 13

measure of asymmetry

- normal distribution has skewness of 0

Question 14

What is kurtosis?

Answer 14

measure of tail density relative to a normal distribution

- normal distribution has kurtosis of 3

Question 15

On SPSS, what is the ideal measurement of skewness and kurtosis for a normally distributed data?

Answer 15

skewness <1

kurtosis between 0-3

Question 16

Platykurtic

Answer 16

kurtosis value <3

no tails

Question 17

Mesokurtic

Answer 17

average scale density that you would expect to see in a normal distribution

Question 18

Laptokurtic

Answer 18

kurtosis value >3
heavy tailed distribution
smaller peak

Question 19

Skewness <0

Answer 19

negatively skewed

to the left

Question 20

Skewness >0

Answer 20

positively skewed

to the right

Question 21

Skewness = 0

Answer 21

normally distributed

Question 22

When do we do a data transformation?

Answer 22

when data is not normally distributed, common to apply a transformation to attempt to improve the normality

Question 23

How to transform a right skewed data? (in order of severity)

Answer 23

• Reciprocal transformation: t = 1/x
• Log transformation: t = log10(x)
• Square root transformation: t = sqrt(x)

Question 24

How to transform a left skewed data? (in order of severity)

Answer 24

Cubic transformation: t = x (cubed)

Square transformation: t = x (sqrd)

Question 25

When can’t we use reciprocal and log transformation?

Answer 25

on 0 value data (add a small constant to every value to fix it)

Question 26

How do we energy adjust macronutrients?

Answer 26

express intake as proportion of total energy intake (% calories from total fat)

Question 27

How do we energy adjust micronutrients?

Answer 27

intake per 1000kcal

Question 28

How do we energy adjust food groups?

Answer 28

intake per 1000kcal

Question 29

What is hypothesis testing?

Answer 29

method of determining if results from your study are meaningful
how likely is it that the results arose by chance

Question 30

What is hypothesis?

Answer 30

educated guess about your variables of interest

Question 31

What is null hypothesis Ho vs alternate hypothesis H1?

Answer 31

Null: there is NO statistically significant difference between the population parameter and the sample statistic being compared

Alternate: statistically significant difference exists between the population parameter and the sample statistic being compared

Question 32

What is a Type 1 error (a)?

Answer 32

the rejection of a true null hypothesis (also known as a “false positive” finding)

Question 33

What is a Type 2 error (B)?

Answer 33

the failure to reject a false null hypothesis (also known as a “false negative” finding)

Question 34

How is rejection of a false null hypothesis represented?

Answer 34

1-B (power of the test) related to the sample size

Question 35

How is acceptance of a true hypothesis represented?

Answer 35

1-a (confidence interval)

Question 36

What is the p value?

Answer 36

probability value

• based off the assumption that H0 is true
• gives the probability that results arose simply by chance.

Question 37

What is alpha?

Answer 37

the significance level: probability of rejecting the null hypothesis when the null is true
1% p<0.01 (2.58)
5% p<0.05 (1.96)
10% p<0.10 (1.65)

Question 38

One-tailed test vs Two-tailed test

Answer 38

one tailed test

is testing the possibility of a relationship in one direction only (comparing means) (u>u0 or u