Applied Inferential Statistics
Offered by
Benaadir Research, Consultancy & Evaluation Center (BRCE)
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LevelAll Levels
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Total Enrolled133
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Duration5 hours
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Last Updated07/12/2024
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CertificateCertificate of completion
35 Cashir
5 Saacadood
Course Certificate
Course Description
Applied Inferential Statistics is a dynamic course designed to introduce you to the principles and techniques of inferential statistics. Building on a foundation of inferential statistics, this course delves into hypothesis testing, various statistical tests, and data analysis methods such as ANOVA, correlation, and regression. You’ll learn to draw conclusions from sample data, making inferences about the population, and gain the skills to apply statistical methods to real-world scenarios.
Why should you take this course?
In the age of big data, the ability to make informed decisions based on statistical analysis is invaluable. This course equips you with the tools to go beyond simple data description and make predictions, test hypotheses, and identify relationships within data. Whether you’re advancing your career, conducting research, or seeking to improve your analytical skills, this course provides essential knowledge and practical experience in inferential statistics.
Who is this course for:
- Students looking to deepen their understanding of statistics.
- Professionals aiming to enhance their data analysis capabilities.
- Researchers requiring advanced statistical tools for their work.
- Anyone interested in applying statistical inference to solve real-world problems.
What you’ll learn:
- The differences between quantitative and qualitative data.
- The distinctions between descriptive and inferential statistics.
- Various measurement scales and their applications.
- Fundamental concepts of descriptive statistics.
- Hypothesis testing and determining statistical significance.
- Performing one-sample tests, independent T-tests, and dependent T-tests.
- Conducting ANOVA (Analysis of Variance) to compare group means.
- Exploring relationships between variables using correlation and regression analysis.
- Applying Chi-square tests for categorical data analysis.
Are there any course requirements or prerequisites?
While there are no strict prerequisites, a basic understanding of high school-level mathematics and familiarity with descriptive statistics will be beneficial.
What you earn after completion of this course:
Upon successfully completing the Applied Inferential Statistics course, you will earn:
- A comprehensive understanding of inferential statistical methods.
- Practical skills in hypothesis testing, T-tests, ANOVA, correlation, regression, and Chi-square tests.
- The ability to make data-driven decisions and inferences.
- Enhanced research and analytical skills applicable across various professional fields.
- A certificate of completion, validating your proficiency in applied inferential statistics.
Material Includes
- 5-hour on-demand video
- 1 Assignments
- 1 downloadable resource
- 20 SPSS FILES
Course Curriculum
Section 1. Course Overview
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Quantitative Vs Qualitative.
15:25 -
Descriptive Vs inferential statistics.
05:16 -
Measurement scales.
04:21 -
Descriptive Statistics.
09:00 -
Hypothesis testing and Statistical Significance.
03:48
Section 2. One simple test
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One simple t test?
04:45 -
One simple t test Example 1
11:47 -
One simple test example 2
10:21 -
One simple t test effect size
07:27
Section 3. independent T test
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independent T test?
05:00 -
Independent T test example 1
09:42 -
independent T test example 2
07:54 -
Independent T test effect size
04:27
Section 4. dependent(Paired) T test
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Dependent T test example 1
03:16 -
Dependent T test example 2
08:14 -
Dependent T test effect size.
04:00
Section 5. ANOVA-analysis of variance.
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What Does Anova-analysis Mean?
11:00 -
Anova between subjects’ example 1
11:29 -
Anova post-hoc test.
11:48 -
Anova between subjects’ example 2.
15:00 -
With in avova example 1.
08:28 -
With in anova post hoc-test.
08:18 -
Within avova example 2.
05:13
Section 6. Correlation and Regression
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Difference between Correlation and Regression.
12:27 -
Correlation example 1
11:30 -
Correlation example 2
05:00 -
Correlation example 3
09:13 -
Regression example 1
11:00 -
Regression example 2
05:19 -
Regression example 3
11:12
Section 7. Chi-square
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Chi-square?
06:28 -
Chi-square goodness to fit test example 1
07:26 -
Chi-square goodness to fit test example 2
05:00 -
Chi-square of independence example 1
10:00 -
Chi-square of independence example 2
05:00
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