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An introduction to statistics, explaining what it is, why it's important, and the differences between descriptive and inferential statistics. It also covers the basics of variables, data, and types of variables, as well as examples and graphical representations of data.

Typology: Study notes

2009/2010

1 / 4

Download Statistics 101: Understanding Data through Descriptive and Inferential Statistics - Prof. and more Study notes Statistics in PDF only on Docsity! 1 STAT 100A Introduction What is Statistics? Statistics is the science of collecting, describing, and interpreting data. Statistics is the science of understanding data. 2 Why Use Statistical Methods? Design: planning how to obtain data to answer the questions of interest Description: Summarizing the data that are obtained Inference: Making decisions and predictions based on the data 3 Descriptive Statistics – utilizes numerical and graphical methods to look for patterns, to summarize, and to present the information in sample data. Inferential Statistics – utilizes sample data to make estimations, decisions, predictions, or other generalizations about a population and measure their reliability. 4 STAT 100A Chapter 1: Describing Data with Graphs Section 1.1: Variables and Data Introduction to Basic Terms population – the set of all measurements of interest to the investigator sample – a subset of the population. variable – a characteristic that changes or varies over time and/or for different individuals or objects under consideration. parameter – a numerical value summarizing the population data. statistic – a numerical value summarizing the sample data. 5 Example: A college dean is interested in learning about the average age of faculty at the college. Match the following. a. population b. sample c. variable d. parameter e. statistic ____ the average age of all faculty members at the college ____ 10 randomly selected ages of faculty members at the college ____ the age of each faculty member at the college ____ all ages of faculty members at the college ____ the average age of the 10 randomly selected faculty members at the college 6 experimental units – the objects on which measurements are taken univariate data – a single variable is measured on a single experimental unit bivariate data – two variables are measured on a single experimental unit multivariate data – more than two variables are measured on a single experimental unit 7 STAT 100A Section 1.2: Types of Variables Two Kinds of Variables qualitative (categorical) variable - places an experimental unit into one of several groups or categories Note: Arithmetic operations, such as addition and averaging, are NOT meaningful for data resulting from a qualitative variable. quantitative (numerical) variable – quantifies an experimental unit Note: Arithmetic operations, such as addition and averaging, are meaningful for data resulting from a quantitative variable. 8 qualitative / / variable \ discrete \ / quantitative \ continuous discrete variable – a quantitative variable that can assume a countable number of values. Intuitively, a discrete variable can assume values corresponding to isolated points along a line interval. That is, there is a gap between any two values. continuous variable – a quantitative variable that can assume an uncountable number of values. Intuitively, a continuous variable can assume any value along a line interval, including every possible value between any two values.