[Coursera] Statistics: Making Sense of Data
Alison Gibbs, Jeffrey Rosenthal (University of Toronto)



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coursera-statistics-making-sense-of-data (167 files)
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lectures/week1-optional/Statistics Making Sense of Data 1.0 Installing R - Mac OSX (210).mp43.45MB
lectures/week1-optional/Statistics Making Sense of Data 1.1 Installing R - PC (155).mp43.18MB
lectures/week1-optional/Statistics Making Sense of Data 1.2 R tutorial for 1.2 Five Number Summary (409).mp45.27MB
lectures/week1-optional/Statistics Making Sense of Data 1.3 R tutorial for 1.3 The Centre of The Data (416).mp46.22MB
lectures/week1-optional/Statistics Making Sense of Data 1.4 R tutorial for 1.4 The Spread of The Data (443).mp46.03MB
lectures/week1-optional/Statistics Making Sense of Data 1.5 R tutorial for 1.5 The Shape of The Data (501).mp47.34MB
lectures/week1-optional/Statistics Making Sense of Data 1.6 R tutorial for 1.6 Categorical Variables (421).mp45.60MB
lectures/week1/Statistics Making Sense of Data 0.0 1.1 Introduction (601).mp48.93MB
lectures/week1/Statistics Making Sense of Data 0.1 1.2 Five Number Summary (844).mp413.66MB
lectures/week1/Statistics Making Sense of Data 0.2 1.3 The Centre of the Data and the Effects of Extreme Values (735).mp49.46MB
lectures/week1/Statistics Making Sense of Data 0.3 1.4 The Spread of the Data (957).mp415.86MB
lectures/week1/Statistics Making Sense of Data 0.4 1.5 The Shape of the Data (1306).mp415.91MB
lectures/week1/Statistics Making Sense of Data 0.5 1.6 Categorical Variables (807).mp415.02MB
lectures/week1/Statistics Making Sense of Data 0.6 1.7 Some Features of Data (739).mp49.79MB
lectures/week2-optional/Statistics Making Sense of Data 3.0 R tutorial for 2.1 Relationships Between Quantitative and Categorical Variables (445).mp46.53MB
lectures/week2-optional/Statistics Making Sense of Data 3.1 R tutorial for 2.2 Examining Relationships Between Two Categorical Variables (809).mp410.94MB
lectures/week2-optional/Statistics Making Sense of Data 3.2 R tutorial for 2.3 Relationships Between Two Quantitative Variables (234).mp43.21MB
lectures/week2/Statistics Making Sense of Data 2.0 2.1 Relationships Between Quantitative and Categorical Variables (1117).mp417.85MB
lectures/week2/Statistics Making Sense of Data 2.1 2.2 Examining Relationships Between Two Categorical Variables (1242).mp418.18MB
lectures/week2/Statistics Making Sense of Data 2.2 2.3 Relationships Between Two Quantitative Variables (940).mp414.24MB
lectures/week2/Statistics Making Sense of Data 2.3 2.4 Data Collection - Sampling (1124).mp415.59MB
lectures/week2/Statistics Making Sense of Data 2.4 2.5 Data Collection - Observational Studies (934).mp412.37MB
lectures/week2/Statistics Making Sense of Data 2.5 2.6 Data Collection - Experiments (1550).mp420.13MB
lectures/week3-optional/Statistics Making Sense of Data 5.0 R tutorial for Week 3 Introduction to Probability (522).mp46.52MB
lectures/week3/Statistics Making Sense of Data 4.0 3.1 The Need for Probability (730).mp415.84MB
lectures/week3/Statistics Making Sense of Data 4.1 3.2 Some Probability Basics (952).mp415.19MB
lectures/week3/Statistics Making Sense of Data 4.2 3.3 Probability Distributions (1659).mp425.88MB
lectures/week3/Statistics Making Sense of Data 4.3 3.4 Long-Run Averages (1406).mp421.26MB
lectures/week3/Statistics Making Sense of Data 4.4 3.5 Sampling Distributions (2526).mp433.09MB
lectures/week4-optional/Statistics Making Sense of Data 7.0 R tutorial for 4.2 Confidence Intervals for Proportions (317).mp44.49MB
lectures/week4-optional/Statistics Making Sense of Data 7.1 R tutorial for 4.3 Sample Size for Estimating a Proportion (230).mp43.21MB
lectures/week4-optional/Statistics Making Sense of Data 7.2 R tutorial for 4.4 Confidence Intervals for Means (213).mp43.22MB
lectures/week4/Statistics Making Sense of Data 6.0 4.1 Introduction to Confidence Intervals (956).mp413.94MB
lectures/week4/Statistics Making Sense of Data 6.1 4.2 Confidence Intervals for Proportions (1043).mp415.47MB
lectures/week4/Statistics Making Sense of Data 6.2 4.3 Sample Size for Estimating a Proportion (1048).mp414.10MB
lectures/week4/Statistics Making Sense of Data 6.3 4.4 Confidence Intervals for Means (1105).mp415.77MB
lectures/week4/Statistics Making Sense of Data 6.4 4.5 Robustness of Confidence Intervals (1930).mp424.96MB
lectures/week5-optional/Statistics Making Sense of Data 9.0 R tutorial for 5.3 Hypothesis Testing for Proportions (314).mp44.87MB
lectures/week5-optional/Statistics Making Sense of Data 9.1 R tutorial for 5.4 Hypothesis Testing for Means (250).mp44.05MB
lectures/week5/Statistics Making Sense of Data 8.0 5.1 Introduction to Statistical Tests (737).mp410.28MB
lectures/week5/Statistics Making Sense of Data 8.1 5.2 The Structure of Statistical Tests (1142).mp414.54MB
lectures/week5/Statistics Making Sense of Data 8.2 5.3 Hypothesis Testing for Proportions (805).mp411.13MB
lectures/week5/Statistics Making Sense of Data 8.3 5.4 Hypothesis Testing for Means (1021).mp414.42MB
lectures/week5/Statistics Making Sense of Data 8.4 5.5 Power and Type I and Type II Errors (1944).mp424.88MB
lectures/week5/Statistics Making Sense of Data 8.5 5.6 Some General Advice About Statistical Tests (1311).mp416.51MB
lectures/week6-optional/Statistics Making Sense of Data 11.0 R tutorial for 6.2 Matched Pairs (425) REPOST.mp46.07MB
lectures/week6-optional/Statistics Making Sense of Data 11.1 R tutorial for 6.3 Comparing Two Proportions (308) REPOST.mp44.19MB
lectures/week6-optional/Statistics Making Sense of Data 11.2 R tutorial for 6.4 Comparing Two Means (243).mp43.79MB
lectures/week6/Statistics Making Sense of Data 10.0 6.1 Connection Between Confidence Intervals and Hypothesis Testing (1126).mp417.26MB
lectures/week6/Statistics Making Sense of Data 10.1 6.2 Matched Pairs (1332).mp418.03MB
lectures/week6/Statistics Making Sense of Data 10.2 6.3 Comparing Two Proportions (1735).mp425.45MB
lectures/week6/Statistics Making Sense of Data 10.3 6.4 Comparing Two Means (1719).mp424.70MB
lectures/week7-optional/Statistics Making Sense of Data 13.0 R tutorial for 7.1 7.2 7.3 (350).mp45.59MB
lectures/week7-optional/Statistics Making Sense of Data 13.1 R tutorial for 7.4 Residual Analysis and Transformations (332).mp45.05MB
lectures/week7/Statistics Making Sense of Data 12.0 7.1 The Linear Regression Formula (933).mp414.48MB
lectures/week7/Statistics Making Sense of Data 12.1 7.2 Regression Coefficients Residuals and Variances (1215).mp417.61MB
lectures/week7/Statistics Making Sense of Data 12.2 7.3 Regression Inference and Limitations (1134).mp416.24MB
lectures/week7/Statistics Making Sense of Data 12.3 7.4 Residual Analysis and Transformations (1100).mp415.59MB
lectures/week8-optional/Statistics Making Sense of Data 15.0 R tutorial for 8.2 8.3 (442).mp46.42MB
lectures/week8/Statistics Making Sense of Data 14.0 8.1 Introduction to the Case Study (1313).mp417.35MB
lectures/week8/Statistics Making Sense of Data 14.1 8.2 Study Design (1453).mp418.46MB
lectures/week8/Statistics Making Sense of Data 14.2 8.3 The First Look at the Data (1748).mp423.40MB
lectures/week8/Statistics Making Sense of Data 14.3 8.4 Formal Analyses and Conclusions (1858).mp423.57MB
lectures/week8/Statistics Making Sense of Data 14.4 8.5 Optional Final Song (439).mp414.69MB
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Type: Course
Tags:

Bibtex:
@article{,
title= {[Coursera] Statistics: Making Sense of Data},
keywords= {},
journal= {},
author= {Alison Gibbs, Jeffrey Rosenthal (University of Toronto)},
year= {2013},
url= {},
license= {},
abstract= {This course is an introduction to the key ideas and principles of the collection, display, and analysis of data to guide you in making valid and appropriate conclusions about the world.




We live in a world where data are increasingly available, in ever larger quantities, and are increasingly expected to form the basis for decisions by governments, businesses, and other organizations, as well as by individuals in their daily lives. To cope effectively, every informed citizen must be statistically literate.


This course will provide an intuitive introduction to applied statistical reasoning, introducing fundamental statistical skills and acquainting students with the full process of inquiry and evaluation used in investigations in a wide range of fields.

},
superseded= {},
terms= {}
}