W1

Central Tendency 

Typical value for a probability distribution or basically averages.

• average, median, and mode

Dispersion 

How many data points deviate from the central tendency

• standard deviation, range, and interquartile range.

Mean (µ or x̄)

Add all numbers ÷ total 

Median

 Line up numbers → pick center value

Mode

Most popular/frequent number

Range 

Max - Min

#1 Con of range

Outliers skew the data

Interquartile range

1. Sort data → Find median (Q2).

2. Find median of lower half (Q1) + upper half (Q3).

3. IQR = Q3 - Q1

Interquartile range #1 con

Must ignore outliers 

Standard deviation

Average distance from the mean

1. Step 1: Add up the squared differences (aka the sum of (x – mean)^2) for each data point.

2. Step 2: Divide by the total set size (n).

3. Step 3: Take the square root of the result.

Population

Entirety of what/who you want to study

Sample

A tiny representation from the population

Sampling methods

• Cluster Sampling

• Stratified Sampling

• Random Sampling

• Convenient Sampling

• Systematic Sampling

Cluster Sampling

Split the population into demographics (e.g., age groups), then randomly sample each.

Systematic Sampling

Every x person picked

Stratified Sampling

Split pop into demographcis (e.g., age groups), then random-sample from each demographic.

Random Sampling

Randomly choose participants

Convenient Sampling

Choose participants based on proximity

Interval data

the data can be categorised, ranked, and evenly spaced

Scales of measurement

nominal, ordinal, interval, and ratio

Nominal data

the data can only be categorised

Ordinal data

the data can be categorised and ranked

Ratio data

the data can be categorised, ranked, evenly spaced, and has a natural zero.