Minitab Mastery: Statistical Analysis and Data Visualization

Focused View

EDUCBA Bridging the Gap

36:43:58

24 View

1. Minitab for Beginners

1. Introduction to Course.mp4

05:13

2. Menu Introduction.mp4

08:01

3. Menu Introduction Continued.mp4

08:45

4. Predictive Analytics Module.mp4

05:21

5. File to Stat Menu.mp4

12:07

6. Stat Menu.mp4

08:12

7. Graph to Assistant.mp4

10:20

8. Graph to Assistant Continued.mp4

09:01

2. Advanced Minitab Training

1. Introduction to Course.mp4

02:57

2. Theory.mp4

08:41

3. Output and Interpretation.mp4

08:57

4. Scatter Plots.mp4

11:11

5. Logistic Regression - Theory.mp4

11:24

6. Regression Model of Fit and Output.mp4

12:32

7. Interpretations and Scatter Plot.mp4

10:28

8. Interpretations and Scatter Plot Continued.mp4

04:58

9. Case Study - Tech Mahindra 1.mp4

08:16

10. Case Study - Tech Mahindra 2.mp4

06:26

11. Case Study - Tech Mahindra 3.mp4

06:50

12. Case Study - Tech Mahindra 4.mp4

08:42

13. Case Study Market Segment.mp4

07:19

14. Multinomial Regression - Theory.mp4

06:22

15. Regression Output Analysis.mp4

13:09

16. Comparison of Linear and Quadratic Regression Models.mp4

12:06

17. Comparison with Scatter Plots.mp4

10:04

18. Comparison of Regression Models and Scatter Plots.mp4

11:39

19. Introduction to Decision Trees.mp4

09:13

20. Principle of Decision Trees.mp4

10:25

21. Decision tree Example.mp4

08:15

22. CART Regression.mp4

11:45

23. Multinomial Response.mp4

11:53

24. Tips and tricks for CART Regression Interpretation.mp4

05:24

25. Diabetes Outputs Observations.mp4

07:11

26. Diabetes Outputs Observations Continued.mp4

10:12

27. Decision Tree and its Limitations.mp4

06:54

3. Advanced Minitab Training

1. Course Contents and Descriptives Output.mp4

16:04

2. Descriptives Continued.mp4

12:20

3. Generating Correlations Output.mp4

12:25

4. Observations and Interpretations.mp4

12:18

5. Histogram Outputs.mp4

12:43

6. Descriptives Interpretations.mp4

11:51

7. Generating Scatter Plots.mp4

06:02

8. Analyzing scatter Plots.mp4

09:41

9. Generate Estimates.mp4

15:01

10. Analysis and Interpretation of Estimates.mp4

08:49

11. Generating and Interpreting scatter Plots.mp4

10:29

12. Import Data.mp4

13:38

4. Minitab GUI and Descriptive Statistics

1. Introduction of Predictive Modeling.mp4

09:40

2. Non Linear Regression.mp4

10:51

3. Anova and Control Charts.mp4

09:57

4. Understanding, Interpretation and implementation using Minitab.mp4

11:00

5. Continue on Interpretation and implementation using Minitab.mp4

10:40

6. Observation.mp4

11:37

7. Results for NAV Prices.mp4

06:47

8. NAV Prices - Observations.mp4

10:27

9. Descriptive Statistics.mp4

08:09

10. Customer Complaints-Observations.mp4

09:57

11. Resting Heart Rate Observations.mp4

08:30

12. Results for Loan Applicant MTW.mp4

09:30

13. More Details on Results for Loan Applicant MTW.mp4

08:48

14. Features of T- Test.mp4

09:33

15. Loan Applicant.mp4

06:16

16. Paired T - Test.mp4

06:47

5. Statistical Analysis using Minitab - Beginners to Beyond

1. Introduction to Minitab.mp4

05:09

2. Types of Data.mp4

09:41

3. Measure of Dispersion.mp4

03:17

4. Descriptive Stats.mp4

10:11

5. Data Sorting.mp4

05:10

6. Histograms.mp4

05:06

7. Pie Charts.mp4

08:47

8. Bar Charts.mp4

05:07

9. Line Graphs.mp4

03:39

10. Scatter plots.mp4

03:31

11. Box Plot.mp4

03:48

12. Discrete Random Variable.mp4

10:31

13. Binomial Distribution.mp4

09:03

14. Normal Distribution.mp4

10:14

15. Normality Test.mp4

06:05

16. Data Transformation.mp4

06:03

17. Sampling and Sample Size.mp4

05:32

18. Sample Size for Estimation.mp4

08:27

19. Parameter Estimation.mp4

08:59

20. Power Analysis.mp4

11:35

21. Measurement System Analysis.mp4

08:08

22. MSA Gage R and R.mp4

03:53

23. MSA Attribute Agreement Analysis.mp4

10:57

24. Process Capability Analysis.mp4

10:20

25. Hypothesis Testing.mp4

11:06

26. Hypothesis Testing Mean.mp4

08:21

27. Paired-T Test.mp4

07:39

28. Anova.mp4

05:26

29. Pareto Analysis.mp4

07:45

30. Correlation.mp4

07:15

31. Regression.mp4

04:55

32. Regression Continue.mp4

11:09

33. Control Charts.mp4

10:36

34. P-Chart.mp4

09:41

6. Minitab - Data Analytics

1. Introduction to Predictive Modelling using Minitab.mp4

10:04

2. Colomn Stasistic.mp4

09:57

3. Window Help and Assistant.mp4

10:33

4. Descriptive Statistics Reliance Example.mp4

10:59

5. Descriptive Statistics Reliance Example Continue.mp4

11:35

6. Descriptive Statistics Infosys Example.mp4

11:53

7. Descriptive Statistics Infosys Example Continue.mp4

10:31

8. T-test-Infosys and Reliance Example.mp4

11:59

9. Chi-Test.mp4

08:58

10. Chi-Test Continue.mp4

09:00

11. Anova.mp4

06:11

12. Anova Continue.mp4

10:05

13. Correlations Part 1.mp4

10:03

14. Correlations Part 2.mp4

07:15

15. Correlations Part 3.mp4

11:01

16. Brief Theory.mp4

13:09

17. Tech Mahindra Analysis.mp4

08:03

18. Tech Mahindra Analysis Continue.mp4

10:37

19. More on Tech Mahindra Analysis.mp4

11:17

20. Tech Mahindra and BSE Descriptive.mp4

06:14

21. Colgate Palmolive.mp4

10:56

22. Colgate Palmolive Analysis.mp4

24:00

23. MS Excel - Regression.mp4

10:47

24. Installation of Analysis Toolpak Addins.mp4

10:21

25. Installation of Analysis Toolpak Addins Continue.mp4

09:32

7. Predictive Analytics & Modeling using Minitab

1. Introduction of Predictive Modeling.mp4

09:40

2. Non Linear Regression.mp4

10:51

3. Anova and Control Charts.mp4

09:57

4. Understanding, Interpretation and implementation using Minitab.mp4

11:00

5. Continue on Interpretation and implementation using Minitab.mp4

10:40

6. Observation.mp4

11:37

7. Results for NAV Prices.mp4

06:47

8. NAV Prices - Observations.mp4

10:27

9. Descriptive Statistics.mp4

08:09

10. Customer Complaints-Observations.mp4

09:57

11. Resting Heart Rate Observations.mp4

08:30

12. Results for Loan Applicant MTW.mp4

09:30

13. More Details on Results for Loan Applicant MTW.mp4

08:48

14. Features of T- Test.mp4

09:33

15. Loan Applicant.mp4

06:16

16. Paired T - Test.mp4

06:47

17. Understanding and Implementation of ANOVA.mp4

10:25

18. Pairwise Comparisons.mp4

07:55

19. Features of Chi - Test.mp4

11:19

20. Preference and Pulse Rate.mp4

09:57

21. Diffe. btw Growth Plan ad Dividend Plan in MF.mp4

07:06

22. Checking NAV Price and Repurchase Price.mp4

06:18

23. Basic Correlation Techniques.mp4

08:33

24. More on Basic Correlation Techniques.mp4

05:50

25. CT Implementation Using Minitab.mp4

10:05

26. Continue on Implemetation using Minitab.mp4

03:19

27. Interpretation of Correlation Values.mp4

06:05

28. Results for Return.mp4

08:42

29. Correlation Values - Observations.mp4

05:55

30. Correlation Values - Interpretations.mp4

08:11

31. Heart Beat - Objective.mp4

05:53

32. Heart Beat - Interpretation.mp4

05:19

33. Demographics and Living Standards.mp4

06:07

34. Demographics and Living Standards - Observation.mp4

06:07

35. Graphical Implementation.mp4

09:02

36. Add Regression Fit.mp4

08:46

37. Scatterplot with Regression.mp4

05:39

38. Scatterplot of Rhdeq vs Rhcap.mp4

04:36

39. Introduction to Regression Modeling.mp4

08:47

40. Identify Independent Variable.mp4

08:32

41. Regression Equation.mp4

07:45

42. Tabulating the Values.mp4

06:11

43. Interpretation and Implementation on Data Sets.mp4

07:57

44. Continue on Interpretation on Database.mp4

08:31

45. Significant Variable.mp4

07:40

46. Calculating Corresponding Values.mp4

08:55

47. Identify Dependent Variable.mp4

09:03

48. Generate Descriptive Statistics.mp4

08:41

49. Scatterplot of Energy Consumption.mp4

06:33

50. Identity Equation.mp4

08:00

51. P - Value and T - Value.mp4

07:11

52. Changes in Tem. and Expansion.mp4

08:17

53. Objective of Stock Prices.mp4

09:19

54. Interpretations of Example 5.mp4

08:40

55. Reliance Return Change.mp4

08:26

56. Generate Predicted Values.mp4

07:36

57. Scatterplot Return RIL.mp4

07:21

58. Basic Multiple Regression.mp4

08:36

59. Basic Multiple Regression Continues.mp4

08:25

60. Basic Multiple Regression - Interpretation.mp4

08:36

61. Generate Basic Statistics.mp4

07:22

62. Working on Scatterplot.mp4

04:02

63. Dependent Variable Objective.mp4

11:30

64. Concept of Multicollinearity.mp4

09:20

65. Identify Dependent Variable Y.mp4

11:41

66. Outputs and Observation.mp4

11:57

67. Interpretations - Example 3.mp4

10:23

68. Calculate with and without Flux.mp4

07:09

69. Scatterplot of Heart FLux Vs Insolation.mp4

06:13

70. Interpretation of Datasets.mp4

12:06

71. Implementation of Datasets.mp4

07:22

72. Example 4 Observations.mp4

09:30

73. Display Descriptive Statistics.mp4

06:41

74. Predicted Values Example 4.mp4

09:55

75. Scatterplot of Example 4.mp4

05:23

76. Calculating IV - Multiple Regression.mp4

09:39

77. Calculating Independent Multiple Regression.mp4

04:20

78. Understanding Basic Logistic Scatter Plot.mp4

10:23

79. Basic Logistic Scatter Plot Continues.mp4

08:15

80. Generation of Regression Equation.mp4

11:29

81. Tabulated Values.mp4

07:20

82. Interpretation and Implementation on Dataset.mp4

10:31

83. Interpretation and Implementation on dataset Continues.mp4

07:48

84. Output and Observation - Tabulated Values.mp4

08:41

85. Business Metrics Example.mp4

06:46

86. Example Two and Three Interpretations.mp4

06:51

87. Regression Equation Group.mp4

07:44

88. Interpretation and Implementation of Scatter Plot.mp4

09:14

89. More on Implementation of Scatter Plot.mp4

05:51

90. Plastic Case Strength.mp4

11:01

91. Separate Equations.mp4

10:59

92. Generation of Predicted Values.mp4

10:30

93. Scatter Plot Strength Vs Temp.mp4

10:13

94. Data of Cereal Purchase.mp4

11:27

95. Children Viewed and RE.mp4

10:18

96. Predicted Values for Individual Customers.mp4

11:47

97. Income Independent Variable.mp4

09:22

98. Example of Credit Card Issuing.mp4

11:13

99. Example Five - Tabulated Values.mp4

09:05

100. Generating Outputs.mp4

08:31

101. Example Five Interpretations.mp4

11:17

102. Situations Income.mp4

09:34

103. Scatterplot.mp4

07:16

104. Scatter Plot Scale.mp4

08:31

105. Using Data Analysis Toolpak.mp4

06:38

106. Implementation of Descriptive Statistics.mp4

08:14

107. Descriptive statistics - Input Range.mp4

07:13

108. Implementation of ANOVA.mp4

06:25

109. Implementation of T - Test.mp4

05:50

110. Implementation Using Correlation.mp4

10:17

111. Implementation Using Regression.mp4

11:51

8. Minitab Practical - Impact of Predictors on Response

1. Introduction to Project.mp4

08:22

2. Case Study - Tech Mahindra.mp4

06:13

3. Regression Model and Output - Tech Mahindra.mp4

09:47

4. Scatter Plot - Tech Mahindra.mp4

11:07

5. Case Study - Tech Mahindra 1.mp4

08:16

6. Case Study - Tech Mahindra 2.mp4

06:26

7. Case Study - Tech Mahindra 3.mp4

06:50

8. Case Study - Tech Mahindra 4.mp4

08:42

9. Comparison of Linear and Quadratic Regression Models.mp4

07:42

10. Comparison with Scatter Plots.mp4

09:24

9. Minitab Practical - Testing of Hypothesis

1. Introduction to Project.mp4

10:06

2. Correlation and Regression Using Minitab.mp4

03:39

3. Weight Versus Waist.mp4

06:41

4. Introduction to Hypothesis Testing.mp4

02:57

5. Hypothesis Testing in Minitab.mp4

06:19

6. Summary Report for Measurement.mp4

03:38

7. Null Hypothesis Part 1.mp4

08:04

8. Null Hypothesis Part 2.mp4

08:03

9. Null Hypothesis Part 3.mp4

04:47

10. P Value.mp4

03:08

Description

Master statistical analysis with Minitab: Learn data visualization, predictive modeling, and hypothesis testing.

What You'll Learn?

Introduction to Minitab: Familiarization with Minitab's interface, tools, and basic functionalities.
Descriptive Statistics: Learning to summarize and interpret data using measures like mean, median, mode, and standard deviation.
Data Visualization: Creating effective graphs and charts such as histograms, scatter plots, and box plots to visually represent data distributions and relations
Hypothesis Testing: Understanding the process of hypothesis testing, including setting up hypotheses, selecting appropriate tests (e.g., t-tests, ANOVA)
Regression Analysis: Applying regression models to analyze relationships between variables, including simple linear regression and multiple regression models.
Predictive Modeling: Using Minitab for predictive analytics, including logistic regression and decision tree analysis to forecast outcomes based on historical
Quality Control and Process Improvement: Applying statistical tools such as control charts and process capability analysis to monitor and improve processes.
Experimental Design: Designing and analyzing experiments using factorial designs and response surface methodologies to optimize processes and products.
Advanced Statistical Techniques: Exploring advanced topics such as time series analysis, non-parametric tests, and multivariate analysis.
Real-World Applications: Applying Minitab skills to real-world case studies and projects across various domains, including healthcare, manufacturing, finance

Who is this for?

Students and Researchers: Seeking to enhance their statistical analysis skills for academic research or thesis work.

Professionals: Working in industries such as healthcare, finance, manufacturing, and marketing who need to analyze data to make informed decisions.

Data Analysts and Scientists: Looking to expand their toolkit with Minitab for comprehensive data analysis and visualization.

Quality Assurance Professionals: Involved in process improvement, Six Sigma projects, and quality control initiatives.

Anyone Interested in Statistics: Individuals keen on learning statistical techniques and applying them practically using Minitab.

What You Need to Know?

Basic Computer Skills: Proficiency in using a computer and familiarity with operating systems (Windows or macOS).

Understanding of Statistics: A basic understanding of fundamental statistical concepts such as mean, median, standard deviation, and hypothesis testing would be beneficial.

Mathematics Knowledge: Comfort with basic mathematics, including algebra and data interpretation.

Software Requirements: Access to Minitab software (version specifics depending on course requirements) installed on your computer or access to a computer lab with Minitab installed.

Access to Data: Availability of datasets for practice and application exercises provided in the course.

Desire to Learn: Motivation and commitment to learn statistical analysis using Minitab for practical applications.

More details

Description
Introduction:
Welcome to the comprehensive course on Minitab, designed to equip learners with the essential skills needed for effective statistical analysis and data visualization. Whether you're new to statistical software or looking to deepen your understanding, this course will guide you through Minitab's capabilities, from basic functions to advanced techniques.
Section 1: Minitab for Beginners
In this section, beginners will be introduced to the foundational aspects of Minitab. Starting with an overview of its interface and menu structure, students will learn how to navigate through essential features and conduct basic statistical operations. Emphasis will be placed on understanding Minitab's role in data analysis and preparing data for further statistical modeling and visualization.
Section 2: Advanced Minitab Training
Moving beyond the basics, this section dives into advanced statistical methodologies using Minitab. Students will explore topics such as regression analysis, logistic regression, and predictive analytics. Practical applications through case studies, including real-world scenarios from companies like Tech Mahindra, will illustrate how to apply Minitab to solve complex business problems and make informed decisions based on data insights.
Section 3: Statistical Analysis using Minitab - Beginners to Beyond
This section focuses on expanding statistical analysis skills using Minitab. It covers a wide range of statistical techniques including hypothesis testing, ANOVA, correlation analysis, and regression modeling. Students will learn how to interpret statistical outputs, generate visualizations like histograms and scatter plots, and conduct advanced data transformations and manipulations.
Section 4: Minitab GUI and Descriptive Statistics
Here, the course delves into the graphical user interface (GUI) of Minitab and its application in descriptive statistics. Students will gain proficiency in using Minitab for tasks such as generating reports, analyzing data distributions, and performing quality control through tools like control charts and ANOVA. Practical exercises will reinforce learning, ensuring students can effectively utilize Minitab for rigorous statistical analysis.
Conclusion:
By the end of this course, students will have developed a robust skill set in using Minitab for statistical analysis across various domains. Whether aiming to enhance professional capabilities or pursue academic research, learners will be equipped with the knowledge and practical experience needed to leverage Minitab's powerful features confidently. This course serves as a gateway to mastering statistical analysis with Minitab, empowering individuals to make data-driven decisions with precision and clarity.
This structured approach provides a clear overview of what each section covers, ensuring learners understand the progression from foundational concepts to advanced applications in statistical analysis using Minitab.
Who this course is for:
Students and Researchers: Seeking to enhance their statistical analysis skills for academic research or thesis work.
Professionals: Working in industries such as healthcare, finance, manufacturing, and marketing who need to analyze data to make informed decisions.
Data Analysts and Scientists: Looking to expand their toolkit with Minitab for comprehensive data analysis and visualization.
Quality Assurance Professionals: Involved in process improvement, Six Sigma projects, and quality control initiatives.
Anyone Interested in Statistics: Individuals keen on learning statistical techniques and applying them practically using Minitab.

User Reviews

Rating

average 0

Total votes0

Focused display

EDUCBA is a leading global provider of skill based education addressing the needs of 1,000,000+ members across 70+ Countries. Our unique step-by-step, online learning model along with amazing 5000+ courses and 500+ Learning Paths prepared by top-notch professionals from the Industry help participants achieve their goals successfully. All our training programs are Job oriented skill based programs demanded by the Industry. At EDUCBA, it is a matter of pride for us to make job oriented hands-on courses available to anyone, any time and anywhere. Therefore we ensure that you can enroll 24 hours a day, seven days a week, 365 days a year. Learn at a time and place, and pace that is of your choice. Plan your study to suit your convenience and schedule.

Udemy

View courses Udemy

Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.