Module 2

Question 1

What is a variable?

Answer 1

Definition: A characteristic that varies across observations.
Types: Categorical (qualitative) & Numeric (quantitative).

Question 2

Types of numeric data

Answer 2

Discrete: Countable values (e.g., number of children).
Continuous: Uncountable values within an interval (e.g., weight).

Question 3

Summarizing categorical data

Answer 3

Group data into categories.
Record frequency.
Calculate relative frequency.
Convert to percentages.

Question 4

Visualizing categorical data

Answer 4

Bar Chart: Bars proportional to frequency.
Pie Chart: Segments proportional to relative frequency.

Question 5

Histogram

Answer 5

No gaps between bars, height reflects frequency.

Question 6

Types of variables

Answer 6

Categorical Variables:
- Represent labels or categories.
- Examples: Marital status, grade in a course, eye color.

Numeric Variables:
- Represent meaningful numbers.
- Subtypes: Discrete & Continuous.

Question 7

Bar charts

Answer 7

Definition: Graphical display of frequencies for categorical data.
Key Points:
Bars can be vertical or horizontal.
Bar length is proportional to frequency.
Bars must have uniform width.

Question 8

Pie chart

Answer 8

Definition: Circular chart divided into segments.
Key Points:
Each segment represents relative frequency.
Good for showing proportions visually.

Question 9

Frequency distribution

Answer 9

Definition: Groups numeric data into intervals.
Steps:
Define intervals.
Count the number of observations in each interval.
Summarize as a table or chart.

Question 10

Relative Frequency

Answer 10

Definition: Proportion of observations in a category or interval.
Formula:

RelativeFrequency=
FrequencyinInterval/TotalFrequency
​

Question 11

Cumulative Frequency

Answer 11

Definition: Total number of observations below a specific interval.
Use Case: Tracks data accumulation across intervals.

Question 12

Cumulative relative frequency

Answer 12

Definition: Proportion of observations below a specific interval.
Key Points: Helps visualize cumulative trends.

Question 13

Histogram

Answer 13

Definition: Graphical representation of numeric data using bars.
Key Characteristics:
No gaps between bars.
Bars represent frequencies for numeric intervals.
Shows shape (symmetric or skewed).

Question 14

Rules for creating graphs

Answer 14

Use the simplest graph possible.
Clearly label axes with scales.
Bars (in bar charts) must be the same width.
Avoid exaggerated vertical axis limits.
Do not stretch or compress the vertical axis.

Question 15

Skewed distribution

Answer 15

Positive Skew: Right tail is elongated.
Negative Skew: Left tail is elongated.
Symmetric: Mirror image around the center.

Question 16

Contingency table

Answer 16

Definition: Table summarizing frequencies of two categorical variables.
Use Case: Displays combinations of categories (e.g., Myers-Briggs type by gender).

Question 17

Stacked column chart

Answer 17

Purpose: Visualize relationships between two categorical variables.
Example: Compare proportions within categories (e.g., Myers-Briggs by gender).

Question 18

Interval width

Answer 18

Definition: Range of values within a group for numeric data.
Interval width = max - min/number of intervals

Question 19

Shape of distribution

Answer 19

Symmetric: Evenly distributed around the center.
Skewed: Data leans left (negative) or right (positive).
Use Case: Histogram visualization.