PRELIMS Flashcards

1
Q

Areas of Statistics

A

Descriptive and Inferential Statistics

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2
Q

Involves the collection, organization and presentation of data.

A

Descriptive Statistics

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3
Q

Involves generalizing from samples to populations performing estimations and hypothesis tests and predictions.

A

Inferential Statistics

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4
Q

The human beings or subjects that are being studied.

A

Population

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5
Q

Characteristic of a population.

A

Parameter

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6
Q

Subset of a population

A

Sample

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7
Q

Characteristic of a sample

A

Statistic

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8
Q

A characteristic or quality that can take on different values.

A

Variable

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9
Q

Data

A

The values or the measurements that the variables can assume.

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10
Q

Qualitative Variables are numerical and can be ordered or ranked. True or False?

A

False. Qualitative Variables refers to categories according to some characteristic. (can either b numerical or non-numeric)

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11
Q

Two types of quantitative variables.

A

Discrete Quantitative and Continuous Quantitative Variables

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12
Q

Countable values

A

Discrete Quantitative Variables

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13
Q

Can be obtained by measuring. Can assume infinite number of values along line interval.

A

Continuous Quantitative Variable

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14
Q

Quantities that can assume just one value.

A

Constants

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15
Q

A variable that the researcher chooses to study in order to assess its possible effects or influence on one or more other variables.

A

Independent Variable

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16
Q

The variable which is presumed to be affected by the IV.

A

Dependent Variable

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17
Q

A secondary IV that modifies the relationship between the primary IV and DV.

A

Moderator Variable

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18
Q

What is a. Mediator Variable?

A

a variable that attempts to explain the relationship between two other variables.

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19
Q

Define Extraneous Variable

A

Independent variables that cannot be controlled.

20
Q

What are the 4 Levels of Measurement

A

Nominal
Ordinal
Interval
Ratio

21
Q

Classifies data into mutually exclusive categories that are “equal”.

A

Nominal

22
Q

Define Ordinal Measurement.

A

Classifies data into mutually exclusive categories which are ranked.

23
Q

Ranks data and there are precise differences between units of measure.

A

Interval Measurement

24
Q

Ratio

A

Has meaningful zero.

25
Q

Quali or Quanti? If Quanti, discrete or continuous?

Area of specialization of BSET students.

A

Quali

26
Q

Defined as the chance of an event is occurring.

A

Probability

27
Q

A variable whose values are determined by chance.

A

Random Variable

28
Q

Describes the probabilities of the possible values of a continuous random variable.

A

Continuous Probability Distribution

29
Q

Consists of the values a random variable can assume and the corresponding probabilities of the values.

A

Discrete Probability Distribution

30
Q

Binomial Distribution

A

outcomes of a binomial experiment.

31
Q

3 Types of Data Presentation

A

Textual, tabular, and graphical forms.

32
Q

Used when the goal of the presenter is to provide background about an event.

A

Textual presentation

33
Q

Most common in representing individual and both quantitative and quali information.

A

Tabular Presentation

34
Q

Divides the data set into 100 equal parts

A

Percentile

35
Q

Divides the data set into ten equal parts.

A

Decile

36
Q

Divides the data set into four equal parts.

A

Quartile

37
Q

The squared deviations from the mean.

A

Variance

38
Q

The square root of the squared deviations from the mean.

A

Standard Deviation

39
Q

The mean of the highest and the lowest score.

A

Midrange

40
Q

Each data value is plotted as a point along a scale of values.

A

Dot plot

41
Q

Line graph that shows cumulative frequencies.

A

Ogive

42
Q

Graph used for nominal data.

A

Bar Graph

43
Q

Graph used for ratio and interval data.

A

Histogram

44
Q

Graph that also used for ratio and interval data. The class mark or midpoint is used as dots connected by lines.

A

Frequency Polygon

45
Q

Quantitative data with separate values: the stem and the leaf

A

Stemplot