MTH4423 ELEMENTARY STATISTICS
3 Credit Hours
Student Level:
This course is open to students on the college level in the freshman year.
Catalog Description of the Course:
MTH4423 ‐ Elementary Statistics (3 hrs.)
[KRSN MAT1020]
An introduction to frequency distributions, measures of central tendency, sampling distribution, t-test and chi-square test, hypothesis testing, and correlation coefficients. This course requires that the student furnish his or her TI-83 or TI-84 series-graphing calculator.
Prerequisite:
Course placement assessment or 21 ACT math score.
Course Classification:
Lecture
Controlling Purpose:
The purpose of this course is to introduce students to the fundamentals of analyzing statistical data from diverse areas of interest.
Learner Outcomes:
Upon completion of the course:
- Students who complete this course with a grade of A or B should be able to interpret sets of statistical data and understand the interpretations made by others.
- The learning outcomes and competencies detailed in this course meet, or exceed the learning outcomes and competencies specified by the Kansas Core Outcomes Project for this course, as sanctioned by the Kansas Board of Regents.
Unit Outcomes for Criterion Based Evaluation:
The following defines the minimum core content not including the final examination period. Instructors may add other content as time allows.
UNIT 1: INTRODUCTION TO STATISTICS
Outcomes: Upon completion of this unit students will be able to discover the nature of statistics and data uses and abuses of statistics, design of experiments, and good sampling methods.
- Distinguish between a population and a sample.
- Distinguish between a parameter and a statistic
- Identify the level of measurement of a set of data.
- Recognize the importance of good sampling methods and the serious deficiency of poor sampling methods.
- Understand the importance of good experimental design, including the control of variable effects, sample size, and randomization.
UNIT 2: DESCRIBING, EXPLORING, AND COMPARING DATA
Outcomes: Upon completion of this unit, the students will be able to consider methods for describing, exploring, and comparing data sets.
- Summarize the data by constructing a frequency table or relative frequency table.
- Construct a histogram dot plot, stem-and leaf plot, pie chart, and Pareto chart.
- Calculate measures of center by finding mean, median, mode, and midrange.
- Calculate measures of variation by finding standard deviation, variance, and range.
- Calculate individual values by using z scores, quartiles, deciles, or percentiles.
- Investigate and explore the spread of data, the center of data, and the range of values by constructing a box plot.
UNIT 3: CORRELATION AND REGRESSION
Outcomes: Upon completion of this unit, the students will be able to investigate relationships and correlations between two or more variables.
- Use scatter diagrams and linear correlation coefficients to decide whether there is a linear correlation between two variables.
- Use methods for finding the equation of the regression line.
- Use the concept of total variation with components of explained and unexplained variation.
- Determine the procedure for obtaining a multiple regression equation.
- Explore the basic concepts of developing a mathematical model including nonlinear functions
UNIT 4: PROBABILITY
Outcomes: Upon completion of this unit, the students will be able to understand the basic concepts of probability theory including notation, basic definitions, addition rule, multiplication rule, fundamental counting rule, factorial rule, permutations rule, and combinations rule.
- Understand basic definitions and notation.
- Understand the probability of any event.
- Find the complement of an event.
- Use of the addition rule for compound events.
- Use of the multiplication rule for compound events.
- Use of the following counting techniques: fundamental counting rule, factorial rule, permutations rule, combinations rule.
UNIT 5: DISCRETE PROBABILITY DISTRIBUTION
Outcomes: Upon completion of this unit, the students will be able to understand the concept of probability and binomial distributions including random variables, computing mean and standard deviation, constructing a probability distribution; and the Poisson probability distribution.
- Understand a random variable has values that are determined by chance.
- Understand a probability distribution consists of all values of a random variable along with their corresponding probabilities.
- Compute the mean and standard deviation to explore a binomial distribution.
- Compute the mean and standard deviation to explore a probability distribution.
- Understand that with a binomial distribution, there are two categories of outcomes and a fixed number of independent trials with a constant probability.
- Compute a Poisson probability distribution which applies to occurrences of some event over a specific interval, and its probabilities.
UNIT 6: NORMAL PROBABILITY DISTRIBUTIONS
Outcomes: Upon completion of this unit, the students will be able to understand continuous probability distributions and focus on the most important category: normal distributions.
- Graph a normal distribution.
- Use a normal distribution to approximate a Binomial Distribution.
- Convert values to standard scores (z scores).
- Verify the solution(s) of the normal distribution.
- Utilize the Central Limit Theorem.
- Understand the Rare Event Rule.
- Utilize the continuity Corrections procedure.
- Determine whether data have a Normal distribution.
UNIT 7: ESTIMATES AND SAMPLE SIZES
Outcomes: Upon completion of this unit, the students will be able to understand the fundamental and important concepts of inferential statistics with a focus on methods for finding estimates of population means, proportions, and variances and develop procedures for finding point estimates, confidence intervals, and required sample size.
- Interpret a Confidence Interval.
- Find Critical Values.
- Determine the Marin of Error.
- Find the Point Estimate and E from a Confidence Interval.
- Use a Confidence Interval to describe, explore, and compare data.
- Estimate the Proportion p.
- Estimate a Population Mean: Large and Small Samples.
- Estimate a Population Variance.
- Use properties of the distribution of the Chi-Square Statistic.
- Find the confidence interval (or interval estimate) for the Population Variance.
- Determine the sample size.
UNIT 8: HYPOTHESIS TESTING
Outcomes: Upon completion of this unit, the students will be able to present methods for testing claims about a population mean, proportion, standard deviation, and variance and draw a conclusion.
- Understand the fundamentals of hypothesis testing.
- Determine the null and alternative hypotheses.
- Find critical values.
- Determine whether it is a two-tail, left-tail, or right-tail test.
- Draw a conclusion from the hypothesis test.
- Use steps in testing a hypothesis.
- Determine the P-Value of testing hypothesis.
- Test claims with confidence intervals.
- Test claims with proportions.
- Test a claim about a mean: large and small samples.
- Test a claim about a standard deviation or variance.
UNIT 9: INTERENCES FROM TWO SAMPLES
Outcomes: Upon completion of this unit, the students will be able to do hypothesis tests considering two samples drawn from two populations.
- Draw inferences about two proportions.
- Draw inferences about two means: Independent and Large Samples.
- Draw inferences about two means: Independent and Large Samples; matched Pairs; Independent and Small Samples.
- Determine confidence Interval Estimates.
- Compare Variation in two samples.
Projects Required:
None
Text Book:
Contact the Bookstore for current textbook.
Materials/Equipment needed:
Text, Graphing Calculator (TI‐83/84 Series)
Attendance Policy:
Students should adhere to the attendance policy outlined by the instructor in the course syllabus.
Grading Policy:
A minimum 40% of the course grade shall consist of proctored assessment(s) of which at least 20% of the course grade shall include a comprehensive departmental final exam.
Maximum Class Size:
Based on classroom occupancy
Course Timeframe:
The U.S. Department of Education, Higher Learning Commission and the Kansas Board of Regents define credit hour and have specific regulations that the college must follow when developing, teaching and assessing the educational aspects of the college. A credit hour is an amount of work represented in intended learning outcomes and verified by evidence of student achievement that is an institutionally‐established equivalency that reasonably approximates not less than one hour of classroom or direct faculty instruction and a minimum of two hours of out‐of‐class student work for approximately fifteen weeks for one semester hour of credit or an equivalent amount of work over a different amount of time. The number of semester hours of credit allowed for each distance education or blended hybrid courses shall be assigned by the college based on the amount of time needed to achieve the same course outcomes in a purely face‐to‐face format.
Refer to the following policies:
402.00 Academic Code of Conduct
263.00 Student Appeal of Course Grades
403.00 Student Code of Conduct
Disability Services Program:
Cowley College, in recognition of state and federal laws, will accommodate a student with a documented disability. If a student has a disability, which may impact work in this class, which requires accommodations, contact the Disability Services Coordinator.
DISCLAIMER: THIS INFORMATION IS SUBJECT TO CHANGE. FOR THE OFFICIAL COURSE PROCEDURE CONTACT ACADEMIC AFFAIRS.
(Updated 2/8/2024)
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