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SYLLABUS
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Syllabus
LECTURE NOTES
UNIT 1-INTRODUCTION TO DATA SCIENCE
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1. Need for Data Science
2.benefits and uses
3.facets of data
4.data science process
5.setting the research goal
6.retrieving data
7.cleansing, integrating, and transforming data
8.exploratory data analysis
9.build the models
10.presenting and building applications.
UNIT 2-DESCRIPTIVE ANALYTICS
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1. Frequency distributions
2. Outliers
3. interpreting distributions
4. graphs – averages
5. describing variability
6. interquartile range
7. variability for qualitative and ranked data
8. Normal distributions
9. z scores –correlation – scatter plots
10. regression – regression line
11. least squares regression line
12. standard error of estimate
13. interpretation of r2
14. multiple regression equations
15. regression toward the mean.
UNIT 3-INFERENTIAL STATISTICS
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1.Populations – samples
2.Random sampling – Sampling distribution
3.Standard error of the mean – Hypothesis testing
4. Z-test – z-test procedure
5. Decision rule – calculations – decisions
6. Interpretations – one-tailed and two-tailed tests
7. Estimation – point estimate
8. Confidence interval_Level conf
9. Effect of sample size
23ADT202-FUNDAMENTALS OF DATA SCIENCE AND ANALYTICS
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