Elementary Statistics - Elementary Statistics CONTENTS 1....

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Elementary Statistics CONTENTS 1. Nomenclature in Statistics Basic words: population, sample, parameter, statistic and variable Sources of data, sampling concepts, sample selection methods Descriptive and inferential statistics 2. Presenting Data Numbers, tables and charts Presenting categorical and numerical data Histograms, charts, scatter diagrams, etc. 3. Descriptive Statistics Measures of central tendency Measures of variation Shapes of distributions 4. Probability and Random Variables Discrete and Continuous Random variables Poisson and Normal distribution Student t and χ 2 distribution 5. Estimation and Significance Confidence Intervals t -test, χ 2 goodness-of-fit 6. Regression Analysis Line and curve fitting Correlation, residuals
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Some Definitions: Statistics Collection of methods for planning experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions. Variable Characteristic or attribute that can assume different values . Random Variable A variable whose values are determined by chance. Type of data sets: Population All subjects possessing a common characteristic that is being studied. Sample A subgroup or subset of the population.
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Example: If we are interested in measuring the salaries of engineers working in metallurgical industry in Turkey, the population data set would be a list of the salaries of every metallurgical engineer in Turkey. The variable here will be the salary of engineers. A sample data set could be obtained by selecting 100 engineers across the country and listing their salaries.
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Type of measurements: Parameter Characteristic or measure obtained from a population . Statistic (not to be confused with Statistics) Characteristic or measure obtained from a sample. Example: Using the engineer salary data sets, we could calculate the average salary for the engineerss. The average calculated from the population data set would be the parameter . The average calculated from the sample of 100 engineers would be a statistic . Notice that unless the population is very small it is probably impossible to gather the population data set, and so it is usually impossible to calculate the parameter we are interested in. The main idea of the science of statistics is that we can get around this difficulty by selecting a sample, calculating the sample statistic, and use the sample statistic to make an estimate of the parameter. Unfortunately, statistical estimates can never be 100% certain. (But they can be 90% or 95% or 99% certain)
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Types of data: Qualitative Variables (Categorical data) Variables which assume non-numerical values. (Eye color, name, etc.) Quantitative Variables (Numerical data) Variables which assume numerical values. (Height, weight, etc.) Discrete Variables Variables which assume a finite or countable number of possible values. Usually obtained by counting.
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Elementary Statistics - Elementary Statistics CONTENTS 1....

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