Statistics for DataScience and Business Analysis

Population and sample

Types of data

Categorical data

Numerical data

Discrete data

Continuous data

Measures of central tendency,asymmetry and variability

Mean,Median,Mode,Standard Deviation

Qulitative data

Quantitative data

Nominal,Ordinal,ratio,Interval

Freaquency distribution table

Absolute frequency

Relative frequency

Cumulative frequency

Pareto Diagram

Histogram

Bins(histogram)

Cross table

Contigency table

Scatter plot

Skewness

Bias and variance

Coefficient of variation

Univariate measure

Multivariate measure

Covariance

Linear correlation coefficient

Correlation

Distribution

Bell curve

Gaussian distribution

Standard normal distribution

Z-statistic

Central limit theorem

Sampling distribution

Standard error

Estimator, Estimate

Point Estimate, interval estimator

Confidence interval

Level of confidence

Z-table,T-statistic,T-table

A rule of thumb

Hypothesis test

Null Hypothesis, Accept and reject Hypothesis

One-tailed,two-tailed test

Significance level

Rejection region

Type-1 error (False positive) and Type-2 Error(False Negative)

Z-score

MU0

P-value

Corelation vs causation

Decomposition

ANOVA

SST

SSR

SSE

R-squared & Adjusted R-squre

Assumptions

F-Test,F-statistic

Linearity

Homoscedasticity

Endogeneity

Autocorrelation

Multicollinearity

Omitted variable bias

Heteroscedasticity

Log Transformation

Semi-log model

Serial correlation