Intro

Question 1

Questionable conclusions could be a result of:

Answer 1

• Insufficient number of data points
• “Bad” data points
• Incomplete data points
• Misinformation

Question 2

Inferential Statistics is….

Answer 2

Inferential Statistics: Drawing conclusions about population based on sample data

Question 3

Why samples?

Answer 3

– Obtaining information on the entire population is expensive
– It may be impossible to examine every member of the population (e.g. battery life)

Question 4

Two Data Types:

Answer 4

– Cross-Sectional Data

– Time-Series Data

Question 5

Cross-Sectional Data:

Answer 5

Cross-Sectional Data: recording characteristics of many subjects at the same point in time, or without regards to differences in time

Question 6

Time-Series Data:

Answer 6

Time-Series Data: over a period of time, certain group of people/events, objects

Question 7

Structured Data:

Answer 7

Well defined structured (length, format), columns/rows with specific characteristics
- numbers, dates, groups of words

Question 8

Unstructured Data:

Answer 8

No defined structured

texts, images, videos, social media posts, blogs

Question 9

Variable:

Answer 9

A characteristic of interest that differs in kind or degree

Question 10

Quantitative Variables:

Answer 10

discrete (countable: # of people) or continuous (uncountable: weight, height, time) variables

Question 11

Measurement Scales for Qualitative Data:

Answer 11

Nominal Scale: CATEGORIZE - values differ by name/label (we can substitute them to mean a level: ratings 1-4 - poor, fair, good, excellent)

Ordinal Scale: CATEGORIZE & ORDER/rank, arithmetic operations

Question 12

Measurement Scales for Quantitative Data:

Answer 12

Interval Scale:

• categorize
• rank
• difference between scale values are meaningful
• Ex. temp scales
• ratios are not meaningful

Ratio Scale:

• categorize
• rank
• arithmetic is meaningful
• value of zero is true zero
• ratios are meaningful

Question 13

What is a frequency distribution table used for?

Answer 13

Frequency distribution table:

• qualitative data
• groups into categories
• Ex. Weather in Seattle for Feb. 2010

Question 14

When do you use a relative frequency table?

Answer 14

When the totals for the frequency distribution table are not the same.
- use percents to compare to get relative frequencies

Question 15

Guidelines for Constructing a Frequency Distribution

Answer 15

• classes are mutually exclusive (no overlap -> signified by no equal)
• classes are exhaustive
• total number of classes in a frequency distribution usually ranges from 5 to 20 (not too much detail, but not too little)

Question 16

Cumulative Relative Frequency:

Answer 16

Relative frequency of the class + the previous ones

Question 17

Histogram

Answer 17

• series of rectangles where each one represents the class
• height = (relative) frequency, shape between them is the same
• no gaps between them

Question 18

Histograms could have 3 distribution shapes:

Answer 18

• Symmetric

- Skewed (positive -tail on left), negative

Question 19

Polygon

Answer 19

Connects each middle-point on the histogram

Question 20

Ogive

Answer 20

Connects a series of neighbouring points (highest point = x-coordinate)
- cumulative relative freq.