LAST EXAM (FINALLY) Flashcards by Angel Amor

Process of selecting a subset of population to make inferences about population

Sampling

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Data values gathered from population

Parameter

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Data values gathered from sample

Statistic

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Most common data gathering methods.
Consisting of set of data questions used for collecting and recording data

Survey

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All units has equal chance to be taken as sample.
Sample being obtained that it will represent the entire population

Probability sampling

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Population is homogeneous and all units are given EQUAL CHANCES to be SELECTED as sample

Simple Random sampling

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Used when population is heterogeneous and quite large

Stratified random sampling

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Population is divided into “strata”

Random sample of units will be selected from different stratum

Stratified random sampling

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Commonly used when objective is to compare groups

Stratified random sampling

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Type of sampling being done by SELECTING EVERY Kth TERM.

Systematic random sampling

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Formula is K = N/n

K= sampling interval
N= population
n= sample size

Systematic random sampling

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Population is divided into cluster along geographic boundaries

Cluster random sampling

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Selecting simple random sample of cluster for which ALL UNITS IN SELECTED CLUSTER WILL BE CONSIDERED

Cluster random sampling

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Not all units will be given chance to be selected

Non-probability sampling

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Selects sample basee on subjective judgment of researchers

Non-probability sampling

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Also known as ACCIDENTAL OR GRAB SAMPLING

Convenience sampling

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Selecting sample from population THAT ARE EASY TO REACH

Convenience sampling

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Selection of respondents is based on the purpose or objective of study

Purposive sampling

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Samples are selected BASED ON PRE DETERMINED CRITERIA SET BY RESEARCHER

Purposive sampling

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Interested in the typicality of units

Model instance sampling

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Based on the researchers judgment, it is also called as judgment sampling

Quota sampling

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Samples should be drawn from experts from the chosen field

Expert sampling

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Diversity are maximum variation
Wide range of respondents

Heterogeneity sampling

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Recruiting acquaintances who meet criteria, also known as referral sampling

Snowball sampling

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To find sample size when the population and margin of error is given

Slovin’s formula

Population is known to be large, but specific value is unknown

Cochran’s formula

N -1

Degree of freedom

Entirety Large group of elements having one common feature

Population

Part of a whole or subset

Sample

Order does not matter

Combination

Order matters

Permutation

Combination formula

cNr = N! / r! (n-r)! Or c( N, n) = N! / (N-n)! n!

You used to compare sample mean and population Sample size should be greater than 30

Z test

Sample size is less than 30

T test

We can get the critical value by first solving for the degree of freedom, which is population minus one denoted as N - 1

T test

Statement or theory that may or may not be true

Hypothesis

Statement about unknown parameter to be broken

Hypothesis

Two types of hypothesis

Null hypothesis Alternative hypothesis

The symbols for this hypothesis: are equal (=), greater than or equal to (≥), and less than or equal to (≤) It has no difference purpose of being rejected

Null hypothesis

Contradicts null hypothesis Symbols used are greater than (>), less than (<) and not equal (≠)

Alternative hypothesis

How are you will check the validity of hypothesis Procedure based on sample evidence, and probability theory

Hypothesis testing

Null hypothesis is rejected when it’s true

Type one error

Probability of committing type one error

Alpha a

Null hypothesis is accepted when it’s false

Type two error

Probability of committing type two error

Beta

Also known as Alpha It is also margin of error This cannot be zero

Level of significance

Commonly used level of significance

0.01 0.05 0.10

It is not equal and non-directional

Two tail test

Greater than > and less than < it is directional

One tail test

Supports the hypothesis and it is located in the middle of the bell shape graph

Acceptance region

It’s support alternative hypothesis and it is located in the shaded region

Critical or rejection reg

Measurable characteristics or attributes of a particular individual or situation being studied

Variables

Contains one variable

Univariate data

Contains one variable

Univariate data

Contains two variables

Bivariate data

Contains two or more variables

Multivariate data

Procedure of describing the relationship between two variables it is described by the scatterplot

Correlation analysis

Graphical representation of relation of two variables

Scatterplot

Can be positive negative or zero

Correlation according to direction

Can be perfect, very high, high, low , negligible or zero

Correlation according to strength

Both variables are high or low

Positive correlation

When variable is high and the other variable is low

Negative correlation

T value is greater than critical value

Significant

T value is less than critical value

Not significant