LAST EXAM (FINALLY) Flashcards
Process of selecting a subset of population to make inferences about population
Sampling
Data values gathered from population
Parameter
Data values gathered from sample
Statistic
Most common data gathering methods.
Consisting of set of data questions used for collecting and recording data
Survey
All units has equal chance to be taken as sample.
Sample being obtained that it will represent the entire population
Probability sampling
Population is homogeneous and all units are given EQUAL CHANCES to be SELECTED as sample
Simple Random sampling
Used when population is heterogeneous and quite large
Stratified random sampling
Population is divided into “strata”
Random sample of units will be selected from different stratum
Stratified random sampling
Commonly used when objective is to compare groups
Stratified random sampling
Type of sampling being done by SELECTING EVERY Kth TERM.
Systematic random sampling
Formula is K = N/n
K= sampling interval
N= population
n= sample size
Systematic random sampling
Population is divided into cluster along geographic boundaries
Cluster random sampling
Selecting simple random sample of cluster for which ALL UNITS IN SELECTED CLUSTER WILL BE CONSIDERED
Cluster random sampling
Not all units will be given chance to be selected
Non-probability sampling
Selects sample basee on subjective judgment of researchers
Non-probability sampling
Also known as ACCIDENTAL OR GRAB SAMPLING
Convenience sampling
Selecting sample from population THAT ARE EASY TO REACH
Convenience sampling
Selection of respondents is based on the purpose or objective of study
Purposive sampling
Samples are selected BASED ON PRE DETERMINED CRITERIA SET BY RESEARCHER
Purposive sampling
Interested in the typicality of units
Model instance sampling
Based on the researchers judgment, it is also called as judgment sampling
Quota sampling
Samples should be drawn from experts from the chosen field
Expert sampling
Diversity are maximum variation
Wide range of respondents
Heterogeneity sampling
Recruiting acquaintances who meet criteria, also known as referral sampling
Snowball sampling
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
