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STA220H1 (9)
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Lecture

# stats lecture notes.docx

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Department
Statistical Sciences
Course
STA220H1
Professor
All Professors
Semester
Fall

Description
LECTURE 1 NOTES STATISTICS is the science of data. It involves collecting, summarizing, organizing, analyzing, and interpreting data. DATA is a set of observations, measurements, or facts. QUANTITATIVE DATA are numbers that occur in a natural and obvious way. QUALITATIVE DATA are not natural numbers and are usually categories. A POPULATION is a set of units that we are interested in studying. AN EXPERIMENTAL UNIT is an object that we are interested in. A VARIABLE is a characteristic or a property of a population unit. A SAMPLE is a subset of the population units. A REPRESENTATIVE SAMPLE shows characteristics typical of the target population. A RANDOM SAMPLE is one where every unit of the population has an equal chance of being selected. DESCRIPTIVE STATISTICS uses graphs and numbers to find patterns and to summarize and present information contained in a data set. INFERENTIAL STATISTICS uses sample data to make generalizations about a larger set of data which is unavailable or unknown to us. A STATISTICAL INFERENCE is a generalization about the population based on the information in a sample. A MEASURE OF RELIABILITY is a statement about the degree of uncertainty of the inference. STEPS IN MAKING AN INFERENCE 1. Define the population. 2. Define the variables of interest. 3. Collect the sample. 4. a) Analyze the sample using descriptive statistics. b) Use this information to make an inference about the population. 5. Give a measure of the reliability of your inference using probability. In observational studies the researcher observes the unit and records the information. In designed experiments the researcher controls the variables and manipulates the units. WAYS TO COLLECT DATA 1. Data from a published source. 2. Data from a designed experiment. 3. Data from a survey. 4. Data from an observational study. LECTURE 2 NOTES Qualitative variables: graphs - pie charts, bar charts Quantitative variables: graphs - dotplots, frequency tables, stem and leaf plots, histograms
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