About Syllabus
Exploring Data

Basics
 Variables,
 Population vs sample,
 Central tendency,
 Variability,
 Position

Charts and Graphs
 Patterns in data
 Dot plots
 Histograms
 Stem plots
 Box plots
 Cumulative plots
 Scatter plots
 Comparing data sets

Regression
 Measurement scales
 linear correlation
 linear regression
 Residual analysis
 Transformations,
 Influential points
 Testing of regression slope and intercept
 Regression Analysis
 Testing of significance of regression equation
 Multiple regression analysis
 Confidence interval for conditional mean of the response variable
 Prediction interval for an observed value of the response variable

Categorical data

Oneway tables, Twoway tables
Descriptive Statistics

Data Condensation
 Classification of DataClassification of Data
 Classes
 Frequency
 Individual data
 Discrete Data
 Continuous / Grouped Data

Measure of Central tendency
 Arithmetic Mean
 Median
 Mode
 Harmonic mean
 Geometric Mean
 Weighted Mean
 Trimmed Mean
 Quartiles
 Deciles
 Percentiles

Measure of Dispersion
 Range
 Coefficient of Range
 Quartile deviation
 Coefficient of quartile deviation
 Variance
 Standard deviation
 Coefficient of Variation (CV).

Skewness and Kurtosis
 Types of Skewness and its measures
 Types of Kurtosis and its measures

Moments
 Raw Moments
 Central Moments
 Relation between raw and central moments.
Probability and Probability Distributions

Surveys
 Data collection
 Sampling methods
 Bias in surveys

Experiments
 Introduction to experiments
 Set
 Subset
 Sample space
 Events and its types,
 Set Identities.

Probability
 Methods of Counting
 Permutation
 Combination
 Probability introduction
 Rules of probability
 Theorems on probability.

Random variables
 Introduction
 Distributions
 Mean and variance
 Independence.

Discrete variables and distributions
 Bernoulli Distribution
 Binomial Distribution
 Negative Binomial Distribution
 Discrete Uniform Distribution
 Poisson Distribution
 Geometric Distribution
 Hypergeometric Distribution
 Multinomial Distribution

Continuous variables
 Continuous Uniform Distribution
 Exponential Distribution
 Normal Distribution
 Standard normal Distribution
 t Distribution,
 Chisquare Distribution
 F Distribution
 Beta Distribution
 Gamma Distribution
 Cauchy Distribution
 Lognormal Distribution
 Weibull Distribution
 Pareto Distribution

Sampling distributions
 Sampling distribution
 Sampling distribution of Mean
 Sampling distribution of Proportion
 Sampling distribution of Variance/Standard Deviation
 Difference between proportions
 Difference between means
 Differnce between Variances
Statistical Inference

Estimation:
 Estimation problems
 Standard error
 Margin of error
 Confidence intervals for:
 Proportions
 Difference between proportions
 Mean
 Difference between means
 Difference between pairs
 Regression slope
 Correlation
 Variance
 Standard Deviation

Hypothesis testing:
 Hypothesis test introduction,
 How to test (Procedure)
 Type IError
 Type IIError
 Power of test

Hypothesis tests Procedures:
 Proportions
 Difference between proportions
 Mean Difference between means
 Difference between pairs (Paired t test)
 Goodness of fit test, Homogeneity
 Chi square test of independence
 Chisquare test of Variance and Standard Deviation
 F test for Equality of Variances
 ANOVA
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The life in hours of an electronic sensor is known to be approximately Normally distributed
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Last month the waiting time at the drive through window of a fastfood restaurant was 3.7 minutes
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Based on a random sample of 1040 adults, the mean amount of sleep per night is 7.73 hours
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A random sample of size 12 from a normal population is given below. 69 74 75 76 78 79 81 83 83 85 86 87
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Consider a Poisson distribution with a mean of three occurrences per time period. (a) Write the appropriate Poisson probability function f(x)
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In a box of 12 light bulbs, it is known that 5 of them are defective. That is, 5 are defective
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