To understand the statistical inferences of Skewness Lecture 18 Test 2 Week 7

To understand the statistical inferences of skewness

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To understand the statistical inferences of Skewness Lecture 18 Test 2 Week 7 Lecture 19 Measures of Dispersion(Karl Pearson co-efficient of Skewness) T-1 R-1 RW-4 Calculation of Skewness using Karl Pearson co- efficient of Skewness To learn the calculation of co- efficient of Skewness and its interpretation SPILL OVER Week 7 Lecture 21 Spill Over MID-TERM Week 8 Lecture 22 Correlation Analysis and Regression Analysis(Scatter Diagram) T-1 R-2 RW-3 Meaning and types of Correlation and its calculations using Scatter Plot To understand the calculation of Correlation using scatter plot Correlation Analysis and Regression Analysis(Scatter Diagram) T-1 R-2 RW-3 Meaning and types of Correlation and its calculations using Scatter Plot To understand the calculation of Correlation using scatter plot Correlation Analysis and Regression Analysis (Deviation taken from Arithmetic Mean) T-1 R-2 RW-3 Meaning and types of Correlation and its calculations using Scatter Plot To understand the calculation of Correlation using scatter plot Correlation Analysis and Regression Analysis (Deviation taken from Arithmetic Mean) T-1 R-2 RW-3 Meaning and types of Correlation and its calculations using Scatter Plot To understand the calculation of Correlation using scatter plot Lecture 23 Correlation Analysis and Regression Analysis(Karl Pearson's and Rank Method) T-1 R-3 RW-3 Calculation of Correlation Coefficient using Karl Pearson's and Spearman's Method To construct Correlation Coefficient for nominal and ordinal data Lecture 24 Correlation Analysis and Regression Analysis (Regression- Lines of Regression) T-1 R-3 RW-3 Meaning of regression,line of regression and coefficient of regression To learn the meaning and applications of regression An instruction plan is only a tentative plan. The teacher may make some changes in his/her teaching plan. The students are advised to use syllabus for preparation of all examinations. The students are expected to keep themselves updated on the contemporary issues related to the course. Upto 20% of the questions in any examination/Academic tasks can be asked from such issues even if not explicitly mentioned in the instruction plan.
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Week 9 Lecture 25 Correlation Analysis and Regression Analysis (Coefficient of Regression) T-1 R-3 R-4 RW-3 Calculation of Coefficient of Regression and its properties To comprehend the statistical inference of Coefficient of Regression Lecture 26 Analysis of Time Series (Concept of time-series and its components) T-1 R-2 RW-2 Meaning and concept of time-series and its components, Method of simple average To grasp basic concept of time series data and its applications Analysis of Time Series (Method of Simple Average) T-1 R-2 RW-2 Meaning and concept of time-series and its components, Method of simple average To grasp basic concept of time series data and its applications Lecture 27 Analysis of Time Series (Method of Semi-Average) T-1 R-3 RW-1 Calculation of Trend line using Method of Semi- Average, Method of Moving Average To forecast the trend
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