These pre-assignments are aligned with the topics in the Calculus I Lecture Notes. On average, there are three pre-assignments per week of lectures. All files are included in a single zip folder as well. With the exception of a few of the application problems, all materials are original. They were funded by the THECB OER Development and Implementation Grant, 2021.

These open-source mathematics assignments are created to be used through the WeBWorK open-source online homework system. The assignments correspond to selected sections in the OpenStax Precalculus textbook. They were created with the help of a 2020-2022 Open Educational Resources (OER) Course Development and Implementation Grant Program through the Texas Higher Education Coordinating Board.

In this section, you will learn the introductory concepts of a simple linear regression analysis including a discussion on the explanatory and response variables in the study. You will learn how to analyze the strength and predictability of regression models.

In this section, you will learn how to analyze the strength and predictability of regression models and how to perform a significance test to statistically see if a linear relationship exists between the explanatory and response variables.

In this section, you will be introduced to important statistical terms. You will learn the difference between a population vs sample, parameter vs. statistic, descriptive vs inferential statistics. You’ll learn how to differentiate between quantitative and qualitative data. You will be introduced to a six-step data analysis process.

In this section you’ll learn how to create and interpret various graphical displays of data. You will be introduced to selecting the appropriate graphical display for the data given. You will learn how to construct and interpret graphs for qualitative data and graphs for quantitative data.

In this section you’ll learn how to calculate measures of spread to include sample variance and standard deviation. You will apply the Empirical Rule to normally distributed data and find measures of relative standing.

In this section, you will be introduced to numerical summaries that describe the center of the distribution to include the mean, median, and mode. You will learn how to construct and interpret a box-and-whisker plot as a way to summarize and display quantitative data.

In this section, you will be introduced to the concept of probability and how it applies to real-world problems. You will learn important vocabulary in probability theory including simple event, event, sample space. You will learn the difference between mutually exclusive and independent events.

In the previous section, you were introduced to the basic concepts of probability theory. In this section you’ll learn how to apply the theory to calculating various types of probabilities using two-way tables (contingency tables).

In this section, you will be introduced to the concept of probability distributions. You will be able to identify the properties and differences between discrete and continuous probability distributions. You will build discrete probability distributions from chance experiments.

In this section, you will be introduced to the concept of sampling distribution including a discussion on the point estimate, standard error, and margin of error. You will learn how to construct and interpret a confidence interval for a population proportion.

In the previous section, you were introduced to the concepts of estimation and constructing confidence intervals. In this section, we will extend this to estimating population means.

In this section, you will be introduced to the process of performing a hypothesis test using a four-step testing procedure. You will also learn about the potential errors in hypothesis testing.

In this section, you will be introduced to the process of performing a hypothesis test using a four-step testing procedure to test a population proportion.

In the previous section, you were introduced to the concepts testing a population proportion. In this section, we will extend this to testing population means.

In this section, you will be introduced to the process of performing a hypothesis test using a four-step testing procedure for two-sample testing. Specifically, you will learn how to perform the large sample test for the difference in population proportions.

In this section, you will learn the process of testing the difference in population means. Specifically, when the population variances are unknown and unequal utilizing the t-statistic.

You will learn the difference between independent and dependent samples. In the previous section, you learned to test two independent samples. In this section, you’ll learn how to test dependent samples, known as a paired t test.