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MCA Statistics Training

Online Instructor led Course

Platform: Google. Skype any suggested


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About the Course

MCA - Statistics

Topics Covered

Unit-1: Descriptive Statistics and Correlation
• Introduction to Statistics;
• Applications in Business & Economics; Data: Summarizing Qualitative & Quantitative Data.
• Exploratory Data Analysis: The Stem-and-leaf Display; Cross Tabulation & Scatter Diagrams;
• Measures of location: Mean, Median, Mode, Percentiles, Quartiles; Measures of Variability: Range,
Inter-quartile Range, Variance, Standard Deviation, Coefficient of Variation;
• Measures of Distribution Shape, Relative Location and Detecting Outliers;
• Exploratory Data Analysis; Weighted Mean & working with Grouped Data
• Measures of Association Between Two Variables; Covariance, Correlation;
Unit-2: Probability & Probability Distribution (25%)
• Introduction to Probability; Experiments, Counting, Rules and Assigning Probabilities; Events and
their Probabilities;
• Some basic Relationships of Probability
• Conditional Probability
• Random Variables: Discrete, Continuous;
• Discrete Probability Distributions; Expected Value & Variance;
• Binomial Probability Distribution
• Poisson Probability Distribution
• Normal Probability Distribution, Normal Approximation of Binomial Probabilities
• Exponential Probability Distribution
Unit-3: Sampling, Sampling Distribution & Interval Estimation (20%)
• Simple Random Sampling, Point Estimation
• Introduction to Sampling Distributions
• Sampling Distribution of 
• Sampling Distribution of 
• Properties of Point Estimation
• Other Sampling Methods
• Population Mean: s Known, s Unknown
• Determining the Sample Size; Population Proportion
Unit-4: Statistical Inference-Testing of Hypothesis & X2 Test chi-square (30%)
• Introduction
• Test of significance for Large Samples: Difference between Small & Large Samples;
• Two-tailed test for Difference between the Means of Two Samples;
• Standard Error of the Difference between two Standard Deviations.
• Tests of significance for Small Samples: The Assumption of Normality;
• Students’ t-Distribution; Properties & Applications of t-Distribution;
• Testing Difference between Means of Two Samples (Independent Samples; Dependent Samples)
• Definition of chi-square; Degrees of freedom; chi-square Distribution; Conditions for Applying chisquare
Test; Uses of chi-square Test; Misuse of chi-square Test
Unit-5: Regression (10%)
• Introduction to Regression; Simple linear Regression Model; least Square Method; Coefficient of
Determination; Correlation Coefficient;
• Model Assumptions; Residual Analysis: Validating Model Assumptions; Outliers and Influential
• Using the Estimated Regression Equation for Estimation & Prediction

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rakesh 12/05/2014

i want to learn some chap of accounts

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About the Trainer

Suresh Patel


4 year academic experience.
Teaching experience in MBA, MCA college for Operation Research and Quantitative techniques, Statistics subject
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Course Id: 10518