Statistics 101: Understanding Data through Descriptive and Inferential Statistics - Prof. , Study notes of Statistics

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.