TMTH 3360 Fall 25 Final Outline

TMTH 3360 FALL Final Exam Review

General Information

• Final Exam Test Date: December 10th, 6:00 PM to 8:00 PM in class

• Review Dates: Monday, December 8th and Tuesday, November 9th from 5:00 PM to 6:30 PM

• Location of Review: Teams

Chapter 1: Learning Objectives (Sections: 1.1)

Constructs/Terminologies to Understand

1. Samples and Populations

   • Random Variable: A variable whose value is subject to variations due to chance (i.e. randomness).

   • Random Sample: A sample that is selected from a population in such a way that every individual has an equal probability of being chosen.

   • Difference Between Sample Data Set and Population Data:

     • Sample Data Set: A subset of the population, which is used to make inferences about the population.

     • Population Data: The entire group of individuals or instances about whom we hope to learn.

   • Normal Curve: A bell-shaped curve that represents the distribution of many types of data; most values cluster around a central region and the probabilities for values further away from the mean taper off equally in both directions.

2. Statistics and Parameters

3. Descriptive and Inferential Statistics

4. Experimental Unit: The smallest division of the experimental material such that any two units may receive different treatments.

5. Variables:

   • Univariate: Involves one variable.

   • Bivariate: Involves two variables.

   • Multivariate: Involves more than two variables.

6. Quantitative and Qualitative Variables

   • Quantitative Variables: Numerical values that represent counts or measurements.

   • Qualitative Variables: Categorical values, which can not be measured in terms of numbers.

7. Discrete and Continuous Variables

   • Discrete Variables: Variables that take on a countable number of values.

   • Continuous Variables: Variables that can take on an infinite number of values within a given range.

8. Categorical Variables: Variables that represent categories or groups.

Chapter 2: Learning Objectives (Sections: 2.1, 2.2, 2.3, 2.4)

Measures of Center

• Mean: The average of a data set calculated by summing all values and dividing by the number of values.

• Median: The middle value of a data set when arranged in ascending or descending order.

• Mode: The value that appears most frequently in a data set.

Measures of Relative Standing

• Z-scores: A statistical measurement that describes a value's relationship to the mean of a group of values. Formula: $Z = \frac{(X - \mu)}{\sigma}$ where

  • $X$ = score

  • $\mu$ = mean of the population

  • $\sigma$ = standard deviation of the population

Chapter 6: Learning Objectives (Sections: 6.1, 6.2, 6.3)

Terminologies to Understand

1. Symbols for Sample and Population

   • Sample Mean ($\bar{x}$) vs. Population Mean ($\mu$)

   • Sample Standard Deviation ($s$) vs. Population Standard Deviation ($\sigma$)

2. Difference Between Sample Proportion and Population Proportion

3. Application of Z-Formulas

   • Used for calculating