Lecture 1 - Introduction, Fundamental Terminology & Basic Concepts

Question 1

What is Statistics (when used as a single noun)?/Define statistics/What is the definition of statistics?

Answer 1

A mathematical technique by which data are organized, treated, and presented for interpretation and evaluation

The science that involves collecting, summarizing, analyzing, presenting and interpreting data. It provides the logical framework which enables the objective evaluation of research questions of interest

Art and science of using quantitative information (data) to gain understanding and to make informed decisions

Question 2

Why is Statistics important?

Answer 2

Statistics is an integral part of scientific research as it allows scientists to estimate population parameters, evaluate hypotheses and make informed decisions based on the uncertain information provided by sample data

(can elaborate individually on estimation of population parameters, evaluation of hypotheses and the making of informed decisions)

Question 3

2 Types of research methods

Answer 3

Quantitative and qualitative

Question 4

5 characteristics of quantitative research

Answer 4

Test theories using numbers

Pre-determined methods

Close-ended questions

Numerical data and analyses

Statistical analysis and interpretation

Question 5

5 characteristics of qualitative research

Answer 5

Test theories using language

Emerging methods

Open-ended questions

Text/image data

Identification of themes and patterns

Question 6

What is measurement?

Answer 6

Process of collecting data i.e. measuring variables

Act of assessing, such as process of comparing a value to a standard, or counting frequency of occurrence of events

Quantitative or qualitative in nature

Question 7

What is evaluation?

Answer 7

Philosophical process of determining the worth of the data

Question 8

What is data?

Answer 8

Result of measurement

Set of measurements made on some part of the universe to address a particular information need or question

No mere collection of dis-joined, unrelated measurements obtained for no particular purpose

Plural

Each measurement is a datum or data point

Question 9

What is a variable? Give an example

Answer 9

Refers to any characteristic of a person, place or an object that can assume more than one value/vary

e.g.

Question 10

What is a constant? Give an example

Answer 10

A characteristic that can assume only one value and never changes

e.g. the distance of a running track

Question 11

4 types/classification of variables [2 sub-classifications under categorical variables (see card 15)]

Answer 11

Quantitative and qualitative/categorical

Independent (predictor) and dependent (criterion)

Question 12

What is a quantitative variable? Give an example

Answer 12

Naturally measured as a number for which meaningful arithmetic operations make sense

Variates differ in magnitude

e.g. Height, Weight, Age, Time, Distance, Temperature, Heart Rate, No.of students in a class, Numerical grades on an exam

Question 13

What is a qualitative/categorical variable? Give an example

Answer 13

Any variable that is not quantitative

No numerical meaning when naturally measured

e.g. RPE scale, Sex, Race, Religion, Pain level on scale

Question 14

2 ways that qualitative/categorical variable can be classified?

Answer 14

scale of measurement: ordinal and nominal scale

Question 15

What is nominal scale? Give an example

Answer 15

Numerical values are just coding and in itself has no true numerical value

values function as labels rather than as numbers

Variates differ in category rather than in magnitude

e.g. Sex, Race, Religion

Question 16

What is ordinal scale? Give an example

Answer 16

ordering in magnitude but interval between values is not interpretable and not equal

e.g. RPE scale, Pain level on scale

Question 17

What is an independent/predictor variable? Give an example

Answer 17

Proposed cause of some effect

Predictor variable

Controlled/manipulated variable (in experiments)

e.g. training program

Question 18

What is an independent/criterion variable? Give an example

Answer 18

Proposed/presumed effect

Dependent on the effects of one or more other variables

An outcome variable (that is observed as a result of the classification, control or manipulation)

Measured not manipulated (in experiments)

e.g. bench press 1RM

Question 19

What is a population? Give an example

Answer 19

A well-defined group of individuals, places, objects, or observations of any size having a unique quality or characteristic

Eg: All social workers in Singapore

Question 20

What is a sample? Give an example

Answer 20

A group of individuals, places, objects or observations selected from a particular population

Eg: Social workers in Singapore who volunteered for a research study

Question 21

Why use a sample?

Answer 21

Limitations and constraints in terms of time, money i.e. not enough time, money, resources, equipment, manpower etc.

Just not possible to conduct experiment on the entire population

Question 22

What is a parameter? Give an example

Answer 22

A characteristic of a population

Describes the population

Population parameter

e.g.

Question 23

What is a statistic (when used a plural noun)? Give an example

Answer 23

A characteristic of a sample used to estimate the population parameter

Describes the sample

Sample statistic: estimate of a population parameter

e.g.

Question 24

2 reasons for learning about the type of variables

Answer 24

1. ) Decide how to interpret the data from that variable
   e. g. Race (nominal): numerical values are just coding and in itself has no true numerical value
   e. g. Race (nominal) or RPE (ordinal): equal differences between numbers do not imply equal differences in the amount of the attribute
2. ) Decide what statistical analysis is appropriate on the values that were assigned

Choice of descriptive or inferential statistical methods depends on the type of variables

Question 25

What is validity/accuracy?

Answer 25

When designing an experiment the investigator must be certain that the study is technically sound i.e. the study must be valid and that one can draw meaningful and useful inferences from the results

Validity should be dealt with early on during the research design to prevent problems that may cast doubt on the implications derived from the results of the study

Related to systematic error

Question 26

What is reliability/precision?

Answer 26

Ability of a measure to produce the consistent results under the same conditions

Consistency of a set of measurements

Extent to which measurement are free of random error i.e. random errors are related to/considered part of the reliability of a measurement

Related to:
Repeatability: the variation arising when all efforts are made to keep conditions constant by using the same laboratory, instrument and operator, and repeating during a short time period

Reproducibility: the variation arising using the same measurement process among different laboratories, instruments and operators over unspecified amount of time

Question 27

What are the 3 things to look at when assessing validity and reliability in quantitative research?

Answer 27

measurement
sampling
study design

Question 28

What is bias?

Answer 28

Any systematic (non-random) error in the design, conduct or analysis of a study

Question 29

What are the 2 type of errors with regards to validity and reliability?

Answer 29

Systematic and random

Question 30

Differentiate between systematic and random error

Answer 30

Systematic: caused by a specific factor in the design, conduct or analysis of a study; consistent in same direction; reproducible inaccuracies; considered part of the validity of a measurement

Random error: caused by unknown and/or unpredictable factors; inconsistent; considered part of the reliability of a measurement

Question 31

Differentiate between sample statistics and population parameters

Answer 31

Population parameter is , while sample statistic is the estimate of a population parameter

Question 32

Differentiate between validity and reliability

Answer 32

Validity is the technical soundness of the experiment and the ability of one to be able to draw meaningful and useful inferences from the results, while reliability is the ability of a measure to produce the consistent results under the same conditions

Validity of an experiment is related to systematic errors, while reliability is related to random errors

Question 33

What are the 4 types of level of measurement scale involved? List from weakest to strongest/highest. Give some examples

Answer 33

Nominal: no ordering e.g. Sex, Race, Gender, Nationality, blood type

Ordinal: ordering exists, but not distance e.g. percentile ranks, grades at school, ranks in a race, letter grade in exam

Interval: distance exists, but not ratios e.g. temperature (in C, F, or R), water level of a river, dates (years), temperature in Celsius, IQ scale, numerical grade on exam

Ratio: ratios exist e.g. temperature in K, weight, driving speed, velocities, lengths, temperature in Kelvin, age