# [Nfb-science] require accessible materials of Statistics:

Vidhya Y vidhya.y93 at gmail.com
Thu Sep 10 15:37:23 UTC 2015

```HI Guys,

if anyone of you are  Studying or have studied Statistics,
and have any of the below mentioned topics in any accessible content,
could you please share?
I need it to study for my exams, and since I am studying in India, I
don't have facilities to get them converted into accessible format.
Course Name: Quantitative Research Methods
list of 1 items
1. Introduction (1 Lecture): Course overview. Fundamentals of
quantitative research methodology. Introduction to the key issues of
research process including
the significance of social research, data collection, processing and
analysis, methodology, and the key principles of scientific
investigation.
list end
Chapter 1-4 from ‘Research Methods for Everyday Life: Blending
qualitative and quantitative approaches’ by Scott Vanderstoep &
Deirdre Johnston
list of 1 items
2. Probability Theory (2 Lectures): Introduction to Sample Space and
Events. Probability Law — Interpretation of probability, Axioms of
probability, Conditional
probability, Random variables, Prior/Posterior probability.
list end
Chapter 1 and 3 from ‘An Introduction to Statistical Inference and Its
Applications’ by Michael Trosset
Chapter 4 from ‘Statistics for Management’ (6th Ed.) by Richard Levin
& David Rubin
list of 1 items
3. Statistical and Distribution Theory (3 Lectures): Discrete random
variables —Basic concepts, Probability Mass Functions. Continuous
random variables
— Basic concepts, Probability Density Functions. Introduction to
Cumulative Distribution Functions. The Binomial distribution, the
Poisson distribution,
Conditional distributions, the Normal distribution and related distributions.
list end
Chapter 4 and 5 from ‘An Introduction to Statistical Inference and Its
Applications’ by Michael Trosset
Chapter 5 from ‘Statistics for Management’ (6th Ed.) by Richard Levin
& David Rubin
list of 1 items
4. Sampling and Sampling Distributions (2 Lectures): Introduction to
Sampling and Sampling distributions, Basic Experimental designs
including experimental
validity and types of variables, Sample size and Standard error.
list end
Chapter 6 from ‘Statistics for Management’ (6th Ed.) by Richard Levin
& David Rubin
Chapter 6 from Probability and Statistics with R by Ugarte et al.
list of 1 items
5. Inferential Statistics (3 Lectures): Understanding statistical
significance. Key types of statistical inference — Point estimation,
Hypothesis testing,
and Set estimation. Discussion of Known/Unknown variances.
One-sample/two-sample tests — t-Tests, Analysis of variance and
covariance.
list end
Chapter 9 from ‘An Introduction to Statistical Inference and Its
Applications’ by
Michael Trosset
Chapter 7, 8 & 9 from ‘Statistics for Management’ (6th Ed.) by Richard
Levin & David Rubin
list of 1 items
6. Basic Statistical Analysis (4 Lectures): Quantification of
population attributes including descriptive statistics and Graphical
representation. Univariate
Analysis — Marginals, Measures of central tendency and variability,
and Grouping and recoding data. Bivariate Analysis — Cross-Tabulation
and Chi-square,
Measures of Association (Correlation). The Plug-in estimates.
list end
Chapter 6, 7 & 13 from ‘An Introduction to Statistical Inference and
Its Applications’ by
Michael Trosset
Chapter 11 from ‘Statistics for Management’ (6th Ed.) by Richard Levin
& David Rubin
Chapter 18 from ‘The Research Imagination: An introduction to
qualitative and quantitative methods’ by Paul Gray, John Williamson,
David Karp & John Dalphin

list of 1 items
7. Multivariate Analysis (4 Lectures): Multivariate Analysis — Simple
Linear Regression including regression line, method of least squares,
regression
model and diagnostics. Limited Dependent Variable Models — Logit and
Probit models.
list end
Chapter 14 from ‘An Introduction to Statistical Inference and Its
Applications’ by
Michael Trosset
Chapter 12 & 13 from ‘Statistics for Management’ (6th Ed.) by Richard
Levin & David Rubin
Chapter 19 from ‘The Research Imagination: An introduction to
qualitative and quantitative methods’ by Paul Gray, John Williamson,
David Karp & John Dalphin

list of 1 items
8. Limit Theorems (2 Lectures): Introduction to the Weak Law of Large
Numbers, Convergence in Probability, The Central Limit Theorem, The
Strong Law of
Large Numbers.
list end
Chapter 8 from ‘An Introduction to Statistical Inference and Its
Applications’ by
Michael Trosset
Chapter 7 from ‘Introduction to Probability’ by Dimitri Bertsekas and
John Tsitsiklis

in case you don't have content from any of these books,
but you have similar content in accessible format, please do share.