This document summarizes key concepts from an introduction to statistics textbook. It covers types of data (quantitative, qualitative, levels of measurement), sampling (population, sample, randomization), experimental design (observational studies, experiments, controlling variables), and potential misuses of statistics (bad samples, misleading graphs, distorted percentages). The goal is to illustrate how common sense is needed to properly interpret data and statistics.
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
Introduction To Statistics
1.
2.
3. Created by Tom Wegleitner, Centreville, Virginia Section 1-1 Overview
4. Overview A common goal of surveys and other data collecting tools is to collect data from a smaller part of a larger group so we can learn something about the larger group. In this section we will look at some of ways to describe data.
5.
6.
7.
8.
9.
10. Created by Tom Wegleitner, Centreville, Virginia Section 1-2 Types of Data
11.
12.
13.
14.
15. Working with Quantitative Data Quantitative data can further be distinguished between discrete and continuous types.
16.
17.
18. Levels of Measurement Another way to classify data is to use use levels of measurement. Four of these levels are discussed in the following slides.
19.
20.
21.
22.
23.
24.
25. Created by Tom Wegleitner, Centreville, Virginia Section 1-3 Critical Thinking
50. Stratified Sampling subdivide the population into at least two different subgroups that share the same characteristics, then draw a sample from each subgroup (or stratum)
51. Cluster Sampling divide the population into sections (or clusters); randomly select some of those clusters; choose all members from selected clusters
![Chapter 1 Introduction to Statistics ,[object Object],[object Object],[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)