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Psychological Statistics > INTRODUCTION AND BASIC CONCEPTS OF STATISTICS > Flashcards

INTRODUCTION AND BASIC CONCEPTS OF STATISTICS Flashcards

1
Q

It is the science that deals with data about the condition of a state or community. It is the organization, analysis, and interpretation of data in pursuit of truth.

A

Statistics

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2
Q

Statistics came from the Latin word _____ meaning state.

A

status

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3
Q

10 Uses of Stats in our Daily Life

A 
Predictions
Testing
Forecasts
Preparedness
Predicting 
Political
Insurance
Consumer
Financial
Sports
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4
Q

2 Branches of Stats

A

Descriptive Statistics

Inferential Statistics

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5
Q

This branch of statistics makes a group of scores comprehensible. It describes the important characteristics of sample data and predict ones Y score based on the X score.

A

Descriptive Statistics

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6
Q

It is the branch of statistics that draws conclusion based on the scores collected and goes beyond them. It decides whether to believe what the sample data indicate about the scores that would be found in the population.

A

Inferential Statistics

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7
Q

Pertains to the entire collection of events.

A

population

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8
Q

Refers to the set of individuals taken from a population.

A

sample

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9
Q

It describes the characteristics of a population of scores.

A

parameter

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10
Q

It is the value that describes a sample.

A

statistics

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11
Q

It is the characteristics that have varying values. it is what researchers try to measure.

A

variable

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12
Q

A possible number or category that a score can have.

A

value

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13
Q

A person’s value on a variable.

A

score

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14
Q

Types of Variables

A

Nominal/Categorical

Numerical

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15
Q

2 Types of numerical or quantitative data

A

Discrete variable

Continuous variable

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16
Q

This variable has a specific value and cannot have values between specific values.

A

Discrete variable

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17
Q

This variable is an infinite number of possible values between any two values.

A

Continuous variable

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18
Q

2 Kinds of Variables

A

Independent variable

Dependent variable

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19
Q

This variable is the one that is manipulated and causes an event to happen.

A

Independent variable

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20
Q

This variable is the one being measured and is the one affected.

A

Dependent variable

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21
Q

This determines how you analyze a given data.

A

Levels of Measurement

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22
Q

4 Levels of Measurement

A

nominal
ordinal
interval
ratio

23
Q

A level of measurement that is categorical and has no ordering.
Ex: marital status, gender, types of car owned

A

nominal

24
Q

A level of measurement that is categorical and follows an order.
Ex: ranking, service quality rating, student letter grades

A

ordinal

25
Q

A level of measurement that has intervals between variables but no true zero .
Ex: Temperature in Fahrenheit, standardized exam scores

A

interval

26
Q

A level of measurement that has intervals between variables and possess an absolute zero.
Ex: age, height, weekly food spending

A

ratio

27
Q

3 tools to summarize data

A

Frequency table
Histograms
Frequency distribution

28
Q

This is a table that summarizes data by listing individuals with varying values for a certain variable.

A

Frequency table

29
Q

A bar-like graph with the values in the horizontal (x) axis and the frequency on the vertical (y) axis.

A

Histogram

30
Q

True or False. Bar graph is used instead of histogram only when data is nominal.

A

True

31
Q

A distribution that displays the pattern of frequencies over various variables.

A

Frequency distribution

32
Q

4 forms/types of Frequency distribution

A

Unimodal distribution
Bimodal distribution
Multimodal distribution
Rectangular distribution

33
Q

It is a distribution that shows one value as the most frequent.

A

Unimodal distribution

34
Q

It is a distribution with two approximately equal frequencies.

A

Bimodal distribution

35
Q

It is a distribution with 2 or more higher frequencies, separated by lower frequencies.

A

Multimodal distribution

36
Q

In this distribution all values have approximately the same frequencies.

A

Rectangular distribution

37
Q

3 types/forms of Frequency distribution

A

Symmetrical distribution
Skewed to the right distribution
Skewed to the left distribution

38
Q

This distribution’s one side is a mirror of the other side.

A

Symmetrical distribution

39
Q

This distribution’s right tail is longer and frequency is higher on the left side.

A

Skewed to the right distribution (positively skewed)

40
Q

This distribution’s left tail is longer and frequency is stacked on the right side.

A

Skewed to the left distribution (negatively skewed)

41
Q

This effect is achieved when the distribution is skewed to the right where the scores are piled up at the low end.

A

floor effect

42
Q

This effect is achieved when the distribution is skewed to the left where the scores are piled up at the high end.

A

ceiling effect

43
Q

It is the Greek term for Kurtosis that means curve.

A

kyrtos

44
Q

This refers to how much the shape of a distribution differs from a normal curve.

A

Kurtosis

normal, heavy-tailed, low-tailed

45
Q

Methods of Data Collection

A 
Interviews
Questionnaires
Experiments
Direct Observations
Use of existing records
46
Q

Methods of Data Presentation

A

Textual method
Tabular method
Graphical method

47
Q

It is presenting data through text.

A

Textual method

48
Q

It is the presentation of data in a systematic manner.

A

Tabular method

49
Q

This presents data in a pictorial form.

A

Graphical method

50
Q

This chart presents historical data.

A

Line chart

51
Q

It is a chart that compares amounts in a time series data.

A

Column chart

52
Q

This chart presents distribution of categorical data.

A

Horizontal Bar chart

53
Q

It is a chart divided into several sections wherein the biggest slice must be placed at 12 o’clock and there should only be less than 6 categories.

A

Pie chart

54
Q

This presents magnitude through symbols and pictures.

A

Pictograph

Psychological Statistics (10 decks)

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