Basic Statistical Concepts The Prerequisites Checklist page on the Department of Statistics website lists a number of courses that require a foundation of basic statistical concepts as a prerequisite.

Basic Statistics for Social and Life Sciences. Designed for undergraduates in the social sciences and life sciences who need to use statistical techniques in their fields.

Descriptive statistics, probability models, sampling distributions. Point and confidence interval estimation, hypothesis testing. Elementary regression and analysis of variance.

Not for credit toward major or minor in Statistics. Students may earn credit for only one of the following courses: Statistical Theory with Application I.

Introduction to fundamental concepts of statistics through examples including design of an observational study, industrial simulation. Theoretical development motivated by sample survey methodology.

Randomness, distribution functions, conditional probabilities. Derivation of common discrete distributions. Statistics as random variables, point and interval estimation. Statistical Theory with Application II. Extension of inferences to continuous-valued random variables.

Maximum likelihood estimators for the continuous case. Simple linear, multiple and polynomial regression. Properties of regression estimators when errors are Gaussian. Class or student projects gathering real data or generating simulated data, fitting models and analyzing residuals from fit.

Basic Statistics for Engineering and Science. For advanced undergraduate students in engineering, physical sciences, life sciences. Comprehensive introduction to probability models and statistical methods of analyzing data with the object of formulating statistical models and choosing appropriate methods for inference from experimental and observational data and for testing the model's validity.

Balanced approach with equal emphasis on probability, fundamental concepts of statistics, point and interval estimation, hypothesis testing, analysis of variance, design of experiments, and regression modeling. For advanced undergraduates in engineering, physical sciences, life sciences.

Comprehensive introduction to modeling data and statistical methods of analyzing data. General objective is to train students in formulating statistical models, in choosing appropriate methods for inference from experimental and observational data and to test the validity of these models.

Focus on practicalities of inference from experimental data. Inference for curve and surface fitting to real data sets. Designs for experiments and simulations. Student generation of experimental data and application of statistical methods for analysis.

Critique of model; use of regression diagnostics to analyze errors.

Practical knowledge of the theory of interest in both finite and continuous time. That knowledge should include how these concepts are used in the various annuity functions, and apply the concepts of present and accumulated value for various streams of cash flows as a basis for future use in: Valuation of discrete and continuous streams of payments, including the case in which the interest conversion period differs from the payment period will be considered.

Application of interest theory to amortization of lump sums, fixed income securities, depreciation, mortgages, etc. Topics covered include areas examined in the American Society of Actuaries Exam 2.

Theory of life contingencies. Life table analysis for simple and multiple decrement functions. Life and special annuities. Life insurance and reserves for life insurance.The standard deviation of a sample is a measure of the amount of variability in the sample.

You can think of it, in general terms, as the average distance from the mean. You can think of it, in general terms, as the average distance from the mean. CHAPTER 3 COMMONLY USED STATISTICAL TERMS There are many statistics used in social science research sample data are often called scores, and the of variables to a smaller number of factors or basic.

Commonly Used Statistical Terms components in a scale or instrument being analyzed. Two. Basic stat general terms sample and. If such a calculated probability is so low that it meets the previously accepted criterion of statistical significance, then we have only one choice: The mode The mode value is the value in a distribution with the highest frequency.

Glossary of Statistical Terms You can use the "find" (find in frame, find in page) function in your browser to search the glossary. Understand the general idea of hypothesis testing -- especially how the basic procedure is similar to that followed for criminal trials conducted in the United States.

Be able to distinguish between the two types of errors that can occur whenever a . Go to Stat > Basic Stat > Paired-t Click the radio button for Samples in Column (this is the default) Click the text box for First Sample (cursor should be in this box).

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Basic Stat General Terms Sample And