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Statistical Analysis Using IBM SPSS Statistics

Location Erbil

Fee 300

Start

Sunday, 6 November 2022

End

Monday, 14 November 2022

Statistical Analysis Using IBM SPSS Statistics

This course provides an application-oriented introduction to the statistical component of IBM SPSS Statistics. Students will review several statistical techniques and discuss situations in which they would use each technique, how to set up the analysis, as well as how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships. Students will gain an understanding of when and why to use these various techniques as well as how to apply them with confidence, interpret their output, and graphically display the results.

Objectives:
  • Analyze and better understand your data, and solve complex business and research problems through a user-friendly interface.

  • Understand large and complex data sets quickly with advanced statistical procedures that help ensure high accuracy and quality decision making.

  • Training on how to enter data, define variables, design questionnaire forms and insert them into the SPSS Statistical program

  • Interpretation of results and how to write statistical reports accordingly

  • You will learn how to interpret the output of a number of different statistical tests

 

Who is this course for?
  • This course is designed for business professionals who want to know how to analyze data. You'll learn how to use IBM SPSS to draw accurate conclusions on your research.

  • Anyone seeking to increase their data analytic skills

  • Anyone who is considering purchasing IBM SPSS Statistics.

 

Prerequisites
  1. Familiarity with basic concepts in statistics, such as measurement levels, mean, and standard deviation.

  2. Familiarity with the windows in IBM SPSS Statistics would be helpful.

Program used
  • IBM SPSS Statistics 26

Course details
  • Total number of hours: 21

  • Duration 7 days

  • Time: 15:00 – 18:00 pm

  • Language: English with Kurdish and Arabic support if needed.

Certification

After completing the training course, students receive a training certificate from MSELECT Academy

Course methodology

An interactive training methodology will be used during the training the participants will have;

  • Experiential Methods.

  • Case studies

Course Modules:

Day 1: Data Handling

  • Creating SPSS data set.

  • Reading the data set from different

  • formats

  • Defining the variable attributes.

  • Different levels of measure data (scale-ordinal-nominal).

  • Creating new variable.

  • Design Questionnaire in SPSS

Day 2: Univariate Data Analysis

Basic descriptive statistics.

  • Measures of central tendency: mean, median, mode.

  • Measures of dispersion: range, standard deviation, variance.

  • Frequency and distribution.

  • Other basic Univariate procedures:(Explore-Cross tabulation-chi-square) Reliability Test.

 Day 3: Transformation the data

  • Computing new variable.

  • Recoding the variable.

  • Filtering the data.

  • Weighted Cases.

  • Replace the missing data

 

Day 4: Graph and Chart

  • Bar chart.

  • Pie chart.

  • Histogram.

  • Scatter plot.

  • Sequences chart.

  • Normal Q-Q plot.

  • Box plot.

  • *Which of them should be used in different situations?

Day 5: Hypothesis Testing in SPSS

Compare Means:

  • One sample t-test

  • Independent sample t-test

  • Paired sample t-test

  • Mean differences between group(s) -One Way ANOVA

 

Day 6: Correlation and Regression Analysis

  • Simple linear.

  • Multiple linear.

 

Day 7: Multivariate Data Analysis

Factor Analysis:

  • KMO test

  • Scree plot.

  • Total variance explained.

  • Component matrix.

  • Rotation.

Payment

Must be made 7 working days before the start of the course. Payment can be made in cash, by bank transfer or through exchange offices.

 

How do I register?

 

You can register by emailing training@mselect.com with the following details:

 

  1. Full Name:

  2. City/Town:

  3. Email Address:

  4. Phone number:

  5. Name of the course: