PSY 104

Question 1

What is measurement?

Answer 1

Measurement is the process of assigning numbers or labels to objects, events, or characteristics according to specific rules, in order to represent quantities, qualities, or categories.

Question 2

5 scales of measurement

Answer 2

• Nominal
• Ordinal
• Interval
• Ratio
• Multidimensional

Question 3

What is nominal scale?

Answer 3

The nominal scale is used for labeling variables without any quantitative value. It categorizes data into distinct groups or categories. Categories are mutually exclusive and have no inherent order. Eg Gender (male, female), blood type (A, B, AB, O)

Question 4

What is ordinal scale?

Answer 4

The ordinal scale arranges data into a specific order or rank but the intervals between ranks are not necessarily equal. It reflects a relative order of values but does not indicate the magnitude of difference between them. Eg Socioeconomic status (low, middle, high), class rankings (first, second, third). It contains 2 degrees of measure; Equivalence and Relative importance (greater than or less than)

Question 5

What is interval scale?

Answer 5

The interval scale orders data and measures the exact differences between values. However, it does not have a true zero point. Equal intervals between values allows for the measurement of the degree of difference but not the ratio. Eg Temperature in Celsius or Fahrenheit, IQ scores

Question 6

What is ratio scale?

Answer 6

The ratio scale is the highest level of measurement, incorporating all the properties of the interval scale, with the addition of a true zero point. Equal intervals and a meaningful zero point, which allows for the computation of ratios. Eg Height, weight, age

Question 7

What is statistics?

Answer 7

Statistics is the science of collecting, analyzing, visualizing, presenting and interpreting data for appropriate decision making.

Question 8

Uses of statistics

Answer 8

• Used to accurately describe the findings of scientific research
• Used in decision making
• Used to make estimations

Question 9

Types of statistics

Answer 9

• DESCRIPTIVE STATISTICS - It involves the collection, presentation, and description of data.
• INFERENTIAL STATISTICS - It refers to the techniques of interpreting the values resulting from the descriptive techniques and then using them to make decisions and draw conclusions about the population.

Question 10

Define population

Answer 10

Population refers to a collection or set of individuals or objects whose properties are to be analyzed.

Question 11

Types of population

Answer 11

• FINITE POPULATION: When the numbers in a population can be physically counted.
• INFINITE POPULATION: When the membership is uncountable.

Question 12

What is a sample

Answer 12

A sample is a subset of individuals, items, or data points selected from a larger population.

Question 13

What is a variable

Answer 13

A variable is a characteristic of interest about each individual element of a population or sample.

Question 14

What is data

Answer 14

Data are raw facts or unprocessed information.

Question 15

Types of data

Answer 15

Numeric and non numeric data

Question 16

What is sampling bias?

Answer 16

Sampling bias occurs when a sample is not representative of the population from which it is drawn, leading to skewed or inaccurate results.

Question 17

What is sampling frame?

Answer 17

A sampling frame is a list or database that includes all the members of a population from which a sample is to be drawn.

Question 18

What is sampling error?

Answer 18

Sampling error is the statistical error that arises when a sample does not truly represent the entire population.

Question 19

What is sample size?

Answer 19

Sample size refers to the number of observations or data points collected in a study or survey. It represents a subset of the population that is used to make inferences about the entire population.

Question 20

What is the law of large numbers?

Answer 20

Law of large numbers is a law that simply states that the more observation you have, the more accurate your estimate of the population mean will be.

Question 21

Types of sampling (Probability sampling)

Answer 21

1. SIMPLE RANDOM SAMPLING: Every member of the population has an equal chance of being selected. For example, drawing names from a hat to select participants for a study.
2. SYSTEMATIC SAMPLING: Every nth member of the population is selected after a random starting point. For example, selecting every 10th person from a list of customers.
3. STRATIFIED SAMPLING: The population is divided into subgroups (strata) based on a specific characteristic, and random samples are taken from each stratum. For example, dividing a population into age groups and randomly sampling from each age group.
4. CLUSTER SAMPLING: The population is divided into clusters, and entire clusters are randomly selected. For example, randomly selecting entire schools from a list and surveying all students in those schools.

Question 22

Types of sampling (Non probability sampling)

Answer 22

1. ACCIDENTAL OR CONVENIENT SAMPLING: Samples are taken from a group that is easy to access or contact. For example, surveying people who pass by on a street corner.
2. PURPOSIVE SAMPLING: The researcher uses their judgment to select participants who are believed to be representative of the population. For example, selecting experts in a field to participate in a specialized study.
3. QUOTA SAMPLING: The researcher ensures certain characteristics are represented in the sample to meet specific quotas. For example, ensuring that a survey includes 50% males and 50% females, but selecting them based on convenience.
4. SNOWBALL SAMPLING: Existing study subjects recruit future subjects from among their acquaintances, useful in hard-to-reach populations. For example, A study on a rare disease where current patients help to find other patients to participate.
5. CAPTIVE SAMPLING: This indicates a kind of forced participation.

Question 23

What is reliability?

Answer 23

Reliability in research refers to the consistency and stability of the results obtained from a measurement or assessment tool. If a research instrument or method produces the same results under consistent conditions over multiple trials, it is considered reliable.

Question 24

What is validity?

Answer 24

Validity is the extent to which a measurement or test accurately reflects or assesses the specific concept it is intended to measure.

Question 25

Methods of establishing reliability of measure

Answer 25

1. TEST RETEST METHOD: Administer the same test to the same group of individuals at two different points in time and then correlate the scores.
2. INTER-RATER RELIABILITY: Have multiple raters or observers evaluate the same set of items independently and then calculate the degree of agreement or correlation between their ratings.
3. ALTERNATE/PARALLEL FORM: Develop two equivalent forms of a test that measure the same construct, administer both forms to the same group of individuals, and correlate the scores. For example, creating two different versions of a vocabulary test and giving both versions to the same group of students.
4. SPLIT-HALF RELIABILITY: Divide the test into two halves (e.g., odd vs. even items) and correlate the scores from each half.

Question 26

Types of validity

Answer 26

1. CONTENT VALIDITY: Assessed through expert evaluation to ensure the measurement covers all aspects of the concept.
2. CONSTRUCT VALIDITY: Evaluated by testing the relationships between the measurement and related constructs, often using statistical methods like factor analysis.
3. CRITERION-RELATED VALIDITY: Measured by comparing the test with an external criterion known to be a valid indicator of the concept, including Predictive Validity and Concurrent Validity.