Introduction to Statistics

Upon successful completion of the course, students will be able to:

• Define the terms population, sample, parameter, and statistic;
• Distinguish between categorical, discrete numerical, and continuous numerical data;
• Explain the proper use of statistics within real-world applications and provide examples of its misuse;
• Describe the basic principles of experimental design and representative sampling methods;
• Create and interpret frequency tables, cumulative frequency tables, histograms, box-and-whisker plots, and scatter plots;
• Calculate and interpret measures of central tendency and variation;
• Use the classical and relative frequency approaches to probability to solve problems;
• Apply the addition, multiplication, and complement rules for probability;
• Define and apply the concepts of conditional probability and independence;
• Compute the expected value, variance, and standard deviation of discrete random variables;
• Determine whether the conditions for a binomial experiment apply and compute probabilities using the binomial distribution;
• Determine probabilities of standard and non-standard normal random variables;
• State and apply the Central Limit Theorem;
• Create and interpret confidence intervals for means, proportions, pairs of means, and pairs of proportions;
• Perform and interpret hypothesis tests for means, proportions, pairs of means, and pairs of proportions;
• Apply the chi-square distribution to evaluate the independence of two variables;
• Compute and interpret the meaning of the correlation coefficient and the coefficient of determination;
• Construct a least-squares regression line and use it to make predictions.