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DATA ANALYSIS DESCRIPTIVELY AND INFERENTIALY WITH SPSS - Coggle Diagram
DATA ANALYSIS DESCRIPTIVELY AND INFERENTIALY WITH SPSS
1. Quantitative data can be grouped into two
DISCRETE DATA
Discrete data is data obtained from the results of counting or counting (not measuring). This data is often referred to as nominal data (Fajri & Herianto, 2021)
CONTINUUM DATA
Continuum data is data obtained from measurement results.
Continuum data are grouped into 3 types, namely ordinal, interval and ratio data.
1. Ordinal data
is data that is tiered or in the form of rankings, for example 1st and 2nd place winners; Class I, II, III etc. This ordinal data can be formed from interval or ratio data.
2. Interval data
is data that is the same distance, but does not have an absolute zero value (absolute). Interval data in social research is usually an instrument (questionnaire) using the Likert scale, Guttman, Semantic Differential, Thurstone. Interval data can be made into ordinal data
3. Ratio
data is data that is the same distance and has an absolute zero value. This data can be added or multiplied, ratio data is the most accurate data. This data can be arranged into interval or ordinal data.
In quantitative research, data analysis is an activity after data is collected from all respondents. Activities in data analysis are
:
1) Grouping data based on variables and types of respondents
2) Tabulate data based on variables from all respondents
3) Presenting data from each variable studied
4) Perform calculations to answer the problem formulation
5) Perform calculations to test the proposed hypothesis.
Data analysis techniques
in quantitative research use statistics. There are
2 statistics for analysis, namely:
1. Descriptive
Statistics are statistics that are used to describe or analyze a statistical research result, but are not used to make broader conclusions or generalizations. Research that does not use a sample, the analysis will use descriptive statistics
2. Inferential statistics
are statistics used to analyze sample data, and the results will be generalized to the population where the sample is taken.
Inferential statistics are divided into two types
1) Parametric statistics
Used to analyze interval or ratio data taken from a normally distributed population, the number of samples must be equal to or more than 30
2) non parametric statistics
, Used to analyze nominal and ordinal data from a population that is freely distributed and the number of samples is less than 30
Difference between descriptive statistics and inferential statistics
Descriptive statistics
are only limited in presenting data in the form of tables, diagrams, graphs, and other quantities. while
inferential statistics
in addition to including descriptive statistics can also be used to estimate and draw conclusions on the population from the sample.
How to enter and process data using SPSS. For your information, here I use SPSS 12.
1) The first thing we do is enter data on the DATA VIEW page in SPSS, then type the values of the variables (Y, X1, and X2).
2) On the VIEV VARIABLES page, in the Name column type the symbol (Y,X1,X2) and in the Label Column type the name of the Variable (Regional,Sales,Promo and Outlet).
3) In the Type column, the Y variable is selected as String type because the data displayed in the DATA VIEW is in the form of letters (regional names) while for the X1, X2, X3 variables the Numeric type is selected because the data displayed is in the form of numbers.
4) Next, to process the data using regression analysis, perform the following steps. Click Analyze, Regression, Linear.
5) Then move Promo(x1),Outlet(x2) into the independent(s) box and Sales (y) in the dependent box.
6.Then click "statistics".
7) Then tick Estimates, Model fit, R Squared change, Descriptives, part and partial correlations, collinerity diagnostics.
Click Continue
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