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STATISTIC OF SOCIAL SCIENCES - Coggle Diagram
STATISTIC OF SOCIAL SCIENCES
WEEK 1: Introduction to statitics
type of statistic
Descriptive Statistics
Methods for organizing, displaying and describing data
by using tables, graphs and summary measures.
Use to manage data sets to allow better presentation
and to assist easier interpretation of data.
Inferential Statistics
methods that that use information gathered from samples to help make decisions or predictions about a population.
Basic Terms
Population
The complete set of individuals, objects, score or cases that is under study
Sample
A subset or fraction of the population of interest
Level of Measurement
Interval
Distance is Meaningful
Ordinal
Attributes can be Ordered
Ratio
Absolute Zero
Nominal
Attributes are only named; weakest
Definition:
WEEK 3: Describing Numerical data
Centrel Tendency
Mode
the number that appear oftenly
Median
average of a set of numbers
Mean
the value occurance lie in the middle of a set of numbers
variation
Range
Interquartile Range
Quartile
Variance
Standart Deviation
Coefficient of Variation
WEEK 4 : Probability
Relative Probability
Probability Laws
Classic Probability
Probability Rule
Contigency Table
Tree Diagram
Multiplication
WEEK 8 : SPSS
Definition
SPSS is a software that widely used as a statistical analytic tool in the field of social science
Surveys
Competitor Analysis
Maket Research
Others..
WEEK 7 : Sampling Distribution
Concept Of Sampling Distribution
sampling distribution of sample means is a distribution obtained by using the means computed from random samples of a specific size taken from a population
Centrel Limit Theorem
States that the distribution of sample means approximates a normal distribution as the sample size gets larger, regardless of the population's distribution.
WEEK 11,12 & 13
Interpret Result in SPSS
Chi-Square
When to use
is used to examine differences between wht you actually find in your study and what you expected to find.
Concept
is a measure of the difference between the observed and expected frequencies of the outcomes of a set of event or variables.
WEEK 2 : Graphing Quantitative and Qualitative Data
Quantitative
Type of Graph
Bar Chart
Pie Chart
Qualitative
Type of Graph
LIne
Frequency Polygon
Histogram Char
WEEK 14 : Interpret Correlation Analysis
Definition
is a method to describe the linear relationship between two different variables. with this method, we can see the patterns and define how linear it is
Types
Positive Correlation
is relationship between 2 variables which the increase of one variable causes an increase for another variable.
Negative Correlation
is the opposite, it is relationship between 2 variables which is the increase of one variables causes a decrease for another variable.
Measuring analysis of correlation
Definition
we can see the patern and direction of two variable from the scatterplot two variable. we need a specific number to define the strenght of the correlation
Methods
Pearson Correlation Coefficient
Spearman Correlation
How to interpret the correlation
the closer to the value of 1, the stronger the relationship between the two variables. when it approaches 0, the assocation between the two variables is geeting weeker. when you get negative value, it means there is a negative vorrelation
WEEK 9 : Estimation
Definition
Estimation is the process of using a scoe from a sample of the population in oder to estimate the scorw of the population. There are three diffrents methods that can be used.
Three Methods
Interval Estimation
The use of sample statistics to determine a potiential range of a apopulation parameter. This intervel is typically stated without stating any degree of confidence
Confidence Interval Estimation
The use of sample statistics to determine a potential range of a population parameter. This confidence interval is stated with a degree of certainty or confidence
Point Estimation
The value of a sample statistic is used as a best guess or quik estimate of the population parameter
WEEK 5 & 6: Dircrete Random Probability
Discrete Random Variable; :
assign a numerical value to the outcomes in the sample space of a random phenomenon
continuous random variable
is not defined as specific values, instead its is defined over an intervel of values and is represented by the area under a curve.
WEEK 10 : Hypothesis Testing
Concept
An assumption made about a population parameter.
Purposes of hypothesis is to make a judgment about the difference between the sample statistic and the population parameter.
The mechabism adopted to make this objective judgment is the core of hypothesis testing.
Process of hypothesis testing
collect data
analyze data to hypothesid
Formulate a hypothesis
Draw conclusion