psandca2

Question 1

is a branch of mathematics that deals with the systematic collection of data, summarizing and presenting data in an organized manner and analyzing data to interpret and draw conclusions from data analysis.

allows us to make sense of and interpret a great deal of information

Answer 1

Statistics

Question 2

involves describing, organizing, and presenting data in an understandable form.
are statistical procedures that are used to summarize, organize, and simplify data (you dont compare just summarize)

Example: Who are your favorite professors in psychology? What is the average attention span of Grade 1 students?
How much money do parents spend on their child’s education on average?
What percentage of juvenile delinquents has an EQ level of below 75?

Answer 2

Descriptive statistics

Question 3

is concerned with analyzing, interpreting, making predictions, inferences, and conclusions about the data. Example: Is there a correlation between gender and mathematical ability

allow us to compare samples and make generalization about the populations where they come from

Example: how does the average attention span of Grade 1 students compare against Grade 2 students?
On average, how does college education expenditure of Class A parents compare against class C parents?

Answer 3

Inferential statistics

Question 4

is a collection of all the elements under consideration in the statistical study. Example: All the COVID-19 patients in the entire Philippines

Is composed of the entire group of individuals that the researcher wants to study

Answer 4

Population

Question 5

is a part or subset of the population from which information is usually collected. Example : COVID-19 patients in Barangay New Era only

• is a small group of individuals selected from a population

Answer 5

Sample

Question 6

is a numerical summary (or characteristic) of the population.

Answer 6

Parameter

Question 7

is a numerical summary (or characteristic) of the sample.

Answer 7

Statistic

Question 8

(plural) are measurements or observations.

Answer 8

Data

Question 9

is a collection of measurements or observations

Answer 9

data set

Question 10

(singular) is a single measurement or observation and is commonly called a score

Answer 10

datum

Question 11

data that have not been processed are called

Answer 11

raw scores.

Question 12

data that are numerical in nature. Examples: Age, height, weight

Answer 12

Quantitative data

Question 13

data that are attributes or characteristics which cannot be subjected to meaningful arithmetic computations. Example: gender, civil status

Answer 13

Qualitative data

Question 14

data assume exact values only and can be obtained by counting. Example: No. of teeth, no. of children in your family
assume exact values only and can be obtained by counting. Example: No. of teeth, no. of children in your family

are separated by individisible categories

ex: person’s age in years, baby’s age in months

Answer 14

Discrete data

Question 15

assume infinite values and can be obtained by measurement. Examples: Scores in an exam, size of one’s shoes

would literally take forever to count

ex: age (25 years, 11 months, 3 weeks, 2 days, 50 minutes, milli sec etc)

Answer 15

Continuous data

Question 16

is a characteristic or property of a population or sample which makes the members different from each other. Example: Gender in a coed school is a variable.

is a characteristic or condition that is not constant (can change or has different values)

Answer 16

Variable

Question 17

is a characteristic or property of a population or sample which makes the members like each other. Example: Gender in a class of all girls is constant.

Answer 17

Constant

Question 18

is the process of assigning individuals, objects, or events to categories according to certain rules.

Answer 18

Measurement

Question 19

weakest level of measurement where names, symbols or numbers are used simply for classifying subjects or categorizing subjects into different groups.

also known as categorical variables (can’t be added, subtracted, divided etc)

Examples: Gender (M=Male, F=Female); Status (1=Single, 2=Married,
3=Widowed, 4+Separated); College Major (art, biology, engineering)

hair color

Answer 19

Nominal (classificatory) scale or level

Question 20

Contains the properties of the nominal scale, but in addition, the numbers assigned to the categories can be ranked or ordered in some low-to-high manner.

• things that can be placed in order

Examples: teacher evaluation (1=poor, 2=fair, 3=good, 4=excellent)
Year level (1=freshman, 2=sophomore, 3=junior, 4=senior), hottest to coldest, riches to poorest, class ranking

Answer 20

Ordinal (or ranking) scale or level

Question 21

Has all the properties of the ordinal scale, but in addition, the distances or intervals between any 2 numbers on the scale are of known size or magnitude.

must have a common and constant unit of measurement but the unit of measurement is arbitrary in that there is no “true zero” point.

ordered numbers with meaningful divisions

ex: temperature, IQ

Answer 21

Interval scale or level

Question 22

Has all the properties of the interval scale, but in addition, it has a “true zero” point which represents none (or the complete absence of the variable being measured).

zero is meaningful

Examples: age (in years), number of correct answers on a test, time (in seconds), zero height means it doesnt exist, income earned, years of education, weight

Answer 22

Ratio scale or level

Question 23

is the process of selecting samples from a given population.

involves the collection, analysis, and interpretation of data gathered from random samples of a population under study

Answer 23

Sampling

Question 24

• every member of the population being sampled has an equal probability of being selected.
  -it uses some form of random selection of research participants from accessible population

Answer 24

Probability sampling

Question 25

• each member of the sample is selected in such a way that each member of the population has an equal chance of being included. This is done through lottery, or through a table of numbers.

Answer 25

Simple random sampling

Question 26

is used when there is a ready list of the total population arranged in order. For example: The researcher would like to choose a sample of size 10 from the population of 500 persons. He divides 500 by 10 and gets 50. This means that he will have to include every 50th member of N after choosing a random start. He chooses 15 as the start so that the samples will include the 15th person in the list, then 65, 115, 165, 215, 265, 315, 365, 415, and 465, until 10 members are chosen.

Answer 26

Systematic sampling

Question 27

is used to ensure different important groups or strata in the population are adequately represented.

the population is divided into subsets or strata

Example: Population of College students is divided into 4

Answer 27

Stratified random sampling

Question 28

is sometimes called area sampling. The population is divided into separate groups called clusters. The clusters are randomly chosen. Each member in the selected cluster is included in the sample.

Answer 28

Cluster Sampling

Question 29

occurs when each member of the population does not have a known chance of being included in the sample. Instead, it is apt to the researcher to select who will be chosen.

does not involve the use of randomization

Answer 29

Non-Probability Sampling

Question 30

researcher chooses the closest, most available, or willing persons as respondents.
-the convenience sample may not be representative of the target population

Answer 30

Convenience sampling

Question 31

researchers select subjects that would meet the quota of each group of his desired sample. Example: The researcher gets 200 smokers and 200 non-smokers.

-stratified convenience sampling strategy

Answer 31

Quota sampling -

Question 32

starts with a selected or known respondent who in turn will point to the next possible respondent, who will in turn point to the next possible respondent (referral), and so on, until data are accumulated.

samples are rare and hard to find

Answer 32

Snowball or chain referral sampling -

Question 33

• subjects are selected based on characteristics that each member possesses. Example: Married vs Unmarried subjects
• is the basis of the researcher’s knowledge of the target population

Answer 33

Purposive sampling

Question 34

a type of sampling where subjects volunteer themselves as in telephone, internet, or text surveys.

Answer 34

Volunteer sampling -

Question 35

With only a handful of scores, data are simply arranged from highest to lowest.

Answer 35

ungrouped frequency distribution.

Question 36

this is a table that shows the scores in groups.

Answer 36

Grouped frequency distribution -

Question 37

a group of scores

Answer 37

Class interval -

Question 38

the end numbers of the class interval

Answer 38

Class limits-

Question 39

the number of scores falling in each class interval

Answer 39

Class frequency -

Question 40

• the difference between the upper limit of the class and the preceding class

Answer 40

Class size

Question 41

the midpoint of a class interval (upper limit + lower limit divide 2)

Answer 41

Class mark -

Question 42

true class limits;

Answer 42

Class boundaries -

Question 43

is defined as halfway between the lower-class limit of the class and the upper-class limit of the preceding class,

Answer 43

Lower class boundary (LCB)

Question 44

is defined as halfway between the upper-class limit of the class and the lower class limit of the succeeding in class.

Answer 44

upper-class boundary (UCB)

Question 45

individual scores are combined into categories, or intervals and the listed along with the frequency socres in each interval

Answer 45

class interval frequency -

Question 46

used to show the distribution of a categorical variables

Answer 46

Bar charts -

Question 47

• comparing levels of nominal variables

Answer 47

Vertical Bar Graphs

Question 48

• commonly used to compare levels of ordinal variables

Answer 48

Horizontal Bar Graphs

Question 49

used to show what part of the whole each level of cateogory variable is

Answer 49

Pie charts -

Question 50

used to visualize the value of variable over time

Answer 50

Line graphs -

Question 51

uses intervals of values and has no gap between bars

Answer 51

Histogram -

Question 52

it uses the actual values of the quantitative variables
(leaf is the ones digit and the stem is the preceeding numbers)

Answer 52

Stem plot/stem and leaf plot -

Question 53

show us how the scores in a set are scattered or distributed around the mean.

Answer 53

Measures of variability or dispersion

Question 54

refers to the highest score minus the lowest score.

Answer 54

Range

Question 55

is a measure of variability that tells us how the scores cluster around the mean.

is the most commonly used and the most important measure of variability.

Answer 55

Standard Deviation -

Question 56

to illustrate the processes of organizing and describing data.

Answer 56

Frequency Distributions

Question 56

individual scores are combined into catergroies, or intervals, and then listed along with the frequency scores in each interval

Answer 56

Class interval frequency

Question 57

The most commonly used measure of central tendency. Adding scorestogether and dividing the sum by the total number scores.

Answer 57

Mean

Question 58

Another measure of central tendency that is used in situations in whic the mean might not be the representative of a distribution
(there’s an extreme score)

Answer 58

Median

Question 59

The third measure of central tendency. It is the score in a distribution that occurs with the greatest frequency

Answer 59

Mode

Question 60

Provides a quantitative measure of the differences between scores in a distribution and describes the degree to which the scores are spread out or clustered together

Answer 60

Variability