The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and
offering a wide range of dental certified courses in different formats.for more details please visit
www.indiandentalacademy.com
This slides introduce the descriptive statistics and its differences with inferential statistics. It also discusses about organizing data and graphing data.
This presentation includes an introduction to statistics, introduction to sampling methods, collection of data, classification and tabulation, frequency distribution, graphs and measures of central tendency.
The presentation is about basic statistical techniques and how statistics can be used effectively in the quality control and process control. It also presents statistical package Minitab version 16 and some of its applications in the field of statistical process control.
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and
offering a wide range of dental certified courses in different formats.for more details please visit
www.indiandentalacademy.com
This slides introduce the descriptive statistics and its differences with inferential statistics. It also discusses about organizing data and graphing data.
This presentation includes an introduction to statistics, introduction to sampling methods, collection of data, classification and tabulation, frequency distribution, graphs and measures of central tendency.
The presentation is about basic statistical techniques and how statistics can be used effectively in the quality control and process control. It also presents statistical package Minitab version 16 and some of its applications in the field of statistical process control.
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Elementary Statistics Practice Test 1
Module 1: Chapters 1-3
Chapter 1: Introduction to Statistics.
Chapter 2: Exploring Data with Tables and Graphs.
Chapter 3: Describing, Exploring, and Comparing Data.
6. Variable Quantitative Qualitative or categorical (e.g. make of a computer, hair colour Gender) Discrete (e.g. number of houses, Cars, accidents Continuous (e.g. length, age, height, Weight, time) Types of variables
7.
8.
9. Population mean (mu) : Sum of all values In the population The population size Sample mean The sample size Sum of all values In the sample MEAN
10. Population variance : Population standard deviation is Numerical Summary : Variability