QM MODULE 1

Question 1

Quantitative Method

Answer 1

• research techniques that focus on numerical data, measurement, and statistical analytics
• used to collect, analyze, and interpret data in a structured and objective manner

Question 2

Quantitative

Answer 2

can be measured or counted
- expressed in numerical form
Ex.: height, weight, temperature, income, number of students

Question 3

Qualitative

Answer 3

• describes characteristics; cannot be measured numerically
  Ex.: colors, opinions, feelings, interview responses

Question 4

Types of Statistical Data

Answer 4

⦁ Quantitative (Numerical) Data
⦁ Qualitative (Categorical) Data

Question 5

Statistical Data

Answer 5

numerical or categorical information collected, analyzed, and used to understand patterns, trends, and relationships

Question 6

⦁ Quantitative (Numerical) Data

Answer 6

represents measurable quantities
- can be further divided into:
⦁ Discrete Data: countable numbers
⦁ Continuous Data: measurable quantities with infinite possible values

Question 7

⦁ Qualitative (Categorical) Data

Answer 7

represents characteristics or labels
- can be further divided into:
⦁ Dichotomic: takes the form of a word with two options (gender)
⦁ Polynomic: takes the form of a word with more than two options (education)

Question 8

Sources of Statistical Data

Answer 8

⦁ Primary Data
⦁ Secondary Data
Variable
Constant

Question 9

⦁ Primary Data

Answer 9

• collected directly by researchers (e.g., surveys, experiments, observations)

Question 10

⦁ Secondary Data

Answer 10

• already collected by others

Question 11

Variable

Answer 11

• an item of interest that can take on many different numerical values

Question 12

Constant

Answer 12

• has a fixed numerical value

Question 13

Levels of Measurement

Answer 13

⦁ Nominal (Categorical)

⦁ Ordinal
⦁ Interval
⦁ Ratio

Question 14

⦁ Nominal (Categorical)

Answer 14

labels without a numerical value
Ex.: eye color, gender

Question 15

⦁ Ordinal

Answer 15

ordered categories where differences are not uniform
Ex.: rating scale, rank in a race

Question 16

⦁ Interval

Answer 16

numerical values where the differences are meaningful, but no true zero
Ex.: temperature in celsius, IQ scores

Question 17

⦁ Ratio

Answer 17

similar to interval, has a true zero
- values can be compared as multiples
Ex.: height, weight, distance, income

Question 18

Types of Quantitative Research

Answer 18

⦁ Descriptive Research
⦁ Correlational Research
⦁ Experimental Research
⦁ Quasi-Experimental Research

Question 19

⦁ Descriptive Research

Answer 19

descibes characteristics of a population
Ex.: census surveys

Question 20

⦁ Correlational Research

Answer 20

examines relationships between variables
Ex.: studying the relationship between exercise and weight loss

Question 21

⦁ Experimental Research

Answer 21

controlled experiments to determine cause and effect
Ex.: testing a new drug’s effectiveness

Question 22

⦁ Quasi-Experimental Research

Answer 22

• similar to experimental but lacks random assignment

Question 23

Types of Statistics

Answer 23

⦁ Descriptive Statistics
⦁ Inferential Statistics

Question 24

⦁ Descriptive Statistics

Answer 24

• summarizing, organizing, and presents data
• helps understand patters within a dataset

Question 25

⦁ Inferential Statistics

Answer 25

- using a sample of data to make predictions about a larger population

Question 26

Sampling

Answer 26

process of selecting a subset (sample) from a larger group (population) for analysis - can be: ⦁ With replacement: a member of the population may be chosen more than one ⦁ Without replacement: a member of the population may be chosen only once

Question 27

Types of Sampling

Answer 27

⦁ Random Sampling (unbiased) - aka “Probability Sampling”

Question 28

Types of Random Sampling

Answer 28

⦁ Simple Random Sampling ⦁ Stratified Sampling ⦁ Systematic Sampling ⦁ Cluster Sampling ⦁ Non-random Sampling (may have bias)

Question 29

Random Sampling

Answer 29

Random sampling ensures that every individual in a population has an equal chance of being selected

Question 30

⦁ Simple Random Sampling

Answer 30

every individual has an equal chance Ex.: drawing names from a hat

Question 31

⦁ Stratified Sampling

Answer 31

population is divided into subgroups, and samples are taken from each Ex.: sampling students from different grade levels

Question 32

⦁ Systematic Sampling

Answer 32

selecting every nth participant Ex.: every 10th customer in a store survey

Question 33

⦁ Cluster Sampling

Answer 33

population is divided into clusters, and entire clusters are selected randomly Ex.: choosing random schools in a city and surveying all students in those schools

Question 34

⦁ Non-random Sampling (may have bias)

Answer 34

- aka “Non-probability Sampling”

Question 35

Techniques in Collecting Quantitative Data

Answer 35

⦁ Observation ⦁ Survey ⦁ Interview ⦁ Experiment ⦁ Content Analysis

Question 36

⦁ Observation

Answer 36

- researchers systematically record behaviors, events, or characteristics

Question 37

Types of Observation:

Answer 37

⦁ Direct Observation (using your own senses) ⦁ Indirect Observation (using technological and electronic gadgets

Question 38

⦁ Survey

Answer 38

- collects numerical data through structured questionnaires or forms

Question 39

⦁ Interview

Answer 39

- research asks participants structured or semi-structured questions to collect data

Question 40

⦁ Experiment

Answer 40

- controlled method used to determine cause and effect relationships

Question 41

⦁ Content Analysis

Answer 41

- analyzing written, spoken, or visual content to quantify data