Section A.2: Univariate analysis

Question 1

Univariate Analysis

Answer 1

Univariate analysis is the simplest form of data analysis. It involves analysing one variable in a dataset to understand its characteristics

Question 2

Dataset

Answer 2

A dataset is a multidimensional (multiple columns) heterogeneous (highly variable - many data types) data structure (a format for organising data)

Question 3

Data structure

Answer 3

A specialised format for organising, processing, retrieving and storing data

Question 4

Univariate data

Answer 4

Univariate data is a type of data which consists of observations on only a single characteristic or attribute, with no cause or relationship between variables.

Question 5

Univariate data classifications (3)

Answer 5

1) ID - Used to uniquely identify a subject.
2) Numerical - Number based. Can be discrete or continuous
3) Categorical - Based on characteristics, can be ordinal or nominal.

Question 6

Univariate analysis techniques (4)

Answer 6

Graphical
Tables
Descriptive statistics
Inferential statistics

Question 7

Univariate data - Graphical analysis (3)

Answer 7

Histogram
Boxplot
Density curve

Question 8

Histogram

Answer 8

A histogram displays the frequency of each value or group of values in numerical data

Question 9

Boxplot

Answer 9

A boxplot summarises data based on the 5-number summary: First quartile, Median, Third quartile, Minimum, and Maximum
It is beneficial for identifying outliers in data

Question 10

Bar chart

Answer 10

Frequency bar charts are a univariate chart used to find the frequency distribution of categories in categorical data

Question 11

Pie charts

Answer 11

Frequency Pie charts are a univariate chart used to show the frequency distribution of categorical data based on “slices” indicating the share of each category

Question 12

What are the two types of descriptive statistics?

Answer 12

Measure of central tendency - mean, median, mode
Measure of variability - range, IQR, variance, standard deviation etc.

Question 13

What is descriptive statistics?

Answer 13

Descriptive statistics involves the generation of summary statistics from a sample of data, used to describe and gain insight into the features of the data set overall.

Question 14

Define measures of central tendency

Answer 14

Measures of central tendency are statistical measures that use a single value to represent the central or typical value for a probability distribution. The three most common are mean, median, and mode.

Question 15

Define measures of variability/dispersion

Answer 15

Measures of variability or dispersion are statistical measures that use a single value to represent the variability or dispersion of values in a data set from the central point. Univariate statistics such as: Range, IQ Range, variance, Quartiles, variance, and standard deviation, are common summary statistics used for this.

Question 16

Define: Mean

Answer 16

The mean is a univariate summary statistic (measure of central tendency) that is calculated given the sum of all data points divided by the number of data points.

Question 17

Define: Median

Answer 17

The median is a univariate summary statistic (measure of central tendency) that is the middle-most value when values of data points are ordered by their magnitude. (Highest to lowest, or lowest to highest)

Question 18

Define: Mode

Answer 18

The mode is a univariate summary statistic (measure of central tendency) that is the most commonly observed value in a distribution. A distribution of data can have 0 or more modes.

Question 19

Define: Range

Answer 19

The range is a univariate summary statistic (measure of variability) that is the

Question 20

Define: Interquartile range

Answer 20

The interquartile range is the difference between the 75th (Q3) and 25th (Q1) percentiles of the data

Question 21

Define: Quartile

Answer 21

A quartile is a quantile which divides the number of data points into four parts based on their values when ordered from lowest to highest

Question 22

Define: Standard deviation

Answer 22

The standard deviation is the square root of the variance, it expresses how much the data points differ from the mean.

Question 23

Define: Variance

Answer 23

The variance of the data is the average of the squared deviations from the mean.