Lesson 2.1: Data, Variables & Samples

Question 1

population

Answer 1

Entire group of individuals or objects to be studied

Question 2

sample

Answer 2

Subset of population that is being studied

Question 3

individual

Answer 3

Person or object that is part of the population being studied

Question 4

statistics

Answer 4

Numerical summary of a sample

Question 5

parameter

Answer 5

Numerical summary of a population

Question 6

inferential statistics

Answer 6

uses methods thattake a result from a sample, extend it to the
population, and measure reliability of the result

Question 7

variable

Answer 7

Variables are characteristics of an individual within a population

Question 8

Qualitative / Categorical Variables

Answer 8

• Allow for classification of individuals based on some attribute
• Cannot perform arithmetic operation on this data

Question 9

Quantitative / Numerical Variables

Answer 9

Provide numerical measure of individuals

Question 10

Qualitative Variables

Types (3)

Answer 10

1. Dichotomous
2. Nominal
3. Ordinal

Question 11

Qualitative Variables

Dichotomous

Answer 11

• Only 2 values
• eg. present/absent, alive/dead

Question 12

Qualitative Variables

Nominal

Answer 12

• Unordered
• eg. A, B, AB, O Blood Type

Question 13

Qualitative Variables

Ordinal

Answer 13

• ordered
• eg. Rate Pain scale (mild to severe)

Question 14

Quantitative Variables

Discrete

Answer 14

• certain values gaps
• eg. sick days per year

Question 15

Quantitative Variables

Continuous

Answer 15

• no value gaps
• eg. blood glucose levels

Question 16

Quantitative / Numerical

Interval Scale

Answer 16

• Numerical data measured using an ordered scale
• Difference between measurement is meaningful
• But does NOT have a true zero

Example: How satisfied are you
from airline service
- Scale: 10, 8, 6 ,4
- ACT or SAT scores

Question 17

Quantitative / Numerical

Ratio Scale

Answer 17

• Numerical data measured using
  an ordered scale
• Difference between
  measurement is meaningful
• And involves a true zero point

Most of the numerical data is ratio type because it has a true
zero
- Example: Height, Weight

Question 18

Categorical Variables in R

Factors

Answer 18

• nominal or ordinal variables
• factor(…) converts string variables to factors
• factor(status, order=TRUE) for ordinal variables
• factors (categories) listed alphabetically by default

Question 19

Categorical Variables in R

Factors: specific order

R code

Answer 19

factor(variable, order=TRUE, levels = c(…)

• eg. status <- factor(status, order=TRUE, levels=c(“Poor”, “Improved”, “Excellent”)
• assigns numbers to factors (eg. 1,2,3 for E, I, P )

Question 20

class(…)

Answer 20

• displays the data type
• eg. ordered, factor, string, numeric, etc.

Question 21

Bias

Types (3)

Answer 21

Sampling Bias
- Technique used to obtain the individuals to be in the sample tends to favor one part of the population

Non response bias
- Individual selected to be in the sample who do not respond

Response Bias
- Answer on the survey do not represent true feeling of the respondent

Question 22

Sampling in R

set.seed()

Answer 22

• creates sampling population
• need to set new population (…) every time

Question 23

sampling

sample(x,y)
sample(x, y, replace=T)

Answer 23

• generate a set size (y) of randomly sampled values (x)
• sample (1:10, 5) = 5 sampled values from range 1:10
• sample(1:10, 5, replace = T) = can replace selected value for reselection

Question 24

nrow(DataFile)

Answer 24

returns number of rows in Data file

Question 25

floor(DataFile)

Answer 25

returns lowest integer value from calculation
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