Course Descriptions & Syllabi

Course Descriptions & Syllabi

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Note: some or all of the courses in the subjects marked as "Transfer" can be used towards a transfer degree: Associate of Science and Arts or Associate of Engineering Science at DACC. Transferability for specific institutions and majors varies. Consult a counselor for this information.

Areas of Study | | MATH115 syllabus




COURSE NUMBER: MATH115
COURSE TITLE:Survey of Statistics (Statistics for non-math majors)
DIVISION:Sciences
IAI CODE(S): M1 902
SEMESTER CREDIT HOURS:3
CONTACT HOURS:60
STUDENT ENGAGEMENT HOURS:135
DELIVERY MODE:Online, In-Person

COURSE DESCRIPTION:

Focuses on statistical reasoning and the solving of problems using real-world data rather than on computational skills. Strong emphasis is on interpretation and evaluation of statistical results that arise from simulation and technology-based computations using technology such as the required TI83/84 Graphing Calculator with a built-in statistical package, and Microsoft Excel spreadsheets. Topics include data collection processes (observational studies, experimental design, sampling techniques, bias), descriptive methods using quantitative and qualitative data, bivariate data, correlation, and least­-squares regression, basic probability theory, probability distributions (normal distributions and normal curve, binomial distribution), confidence intervals and hypothesis tests using p-values.

This course is designed as a general survey of basic statistical methods. Emphasis is placed on methodology, and applications to biological, social, and management sciences are stressed to underscore the practicality of the material.


PREREQUISITES:
A student in this course should be college-ready in mathematics by having completed: Intermediate Algebra (MATH108) with a C or better, placement, co-requisite course, multiple measures, transitional mathematics competencies, or completing Applied Mathematical Concepts (MATH107) with a C or better.

NOTES:

STUDENT LEARNING OUTCOMES:
Upon completion of this course, students will be able to:
  • Write, define and explain all statistical symbols and abbreviations used in the course
  • Clearly write interpretation of solutions to statistical application problems.
  • Show step-by-step work and provide explanation for how to both setup and generate a statistical solution for application problems.
  • Correctly make use of graphing calculators and /or spreadsheet software to complete statistical analysis.
  • Determine and state from any initial question the meaning and/or definition of all given statistics, and state what formulas and techniques will be used to generate solution.
  • Write or state definitions of, and be able to properly use in discussions (oral or written), basic statistical terminology.
  • Create statistical graphs from data by using technology.
  • Interpret and explain trends from statistical graphs.
  • Calculate basic statistics from data, both manually and by using technology.
  • Interpret and explain basic statistical information, with regard to patterns and outliers.
  • Apply basic probability concepts in calculations regarding probability distributions
  • Define and/or state the Empirical Rule.
  • Define and perform calculations on a normal distribution.
  • Define and perform calculations on a binomial distribution.
  • Graph, create, and perform calculations on linear models from data using regression techniques.
  • Differentiate between the Correlation Coefficient and the Coefficient of Determination.
  • Differentiate between evidence for linearity and insufficient evidence for linearity using correlation.
  • Differentiate between Outliers and Influential Observations.
  • Calculate the population mean estimate through the use of confidence intervals.
  • Explain inferences and test hypotheses on population means using hypothesis tests with the Z and t test statistics
  • Explain the logical step-by-step setup, and solution process for statistical application problems clearly and precisely.
  • Clearly state the interpretation of a solution
  • Calculate answers to arithmetic and data oriented statistical problems using the TI series of statistical calculator and spreadsheet software

TOPICAL OUTLINE:
  • Introduction to Statistics [3 contact hours]
    • Background
    • Uses and abuses of statistics
    • The nature of data
    • Methods of sampling
  • Descriptive Statistics [8 contact hours]
    • Summarizing data
    • Data graphs
    • Measure of centrality
    • Measures of dispersion
    • Measures of position
  • Basic Sampling [3 contact hours]
    • Basic definitions
    • Bias
    • Sampling techniques
  • Probability [5 contact hours]
    • Fundamental definitions
    • Addition rule
    • Multiplication rule
  • Probability Distributions [15 contact hours]
    • Random variables
    • Binomial Distribution
    • Standard normal distribution
    • Non-standard distribution
    • The central limit theorem and the sampling distribution of the sample mean
  • Confidence Intervals [6.5 contact hours]
    • Estimation of a population mean
    • Estimation of a population proportion
    • Sample size considerations
  • Hypothesis Testing [6.5 contact hours]
    • Fundamental definitions
    • Testing a claim about a population mean: large samples
    • Testing a claim about a population mean: small samples (t-test)
    • Testing a claim about a proportion
  • Linear Regression [6 contact hours]
    • Fundamental definitions
    • Correlation and Pearson-R correlation coefficient
    • Regression (linear)

TEXTBOOK / SPECIAL MATERIALS:

The Basic Practice of Statistics, 8th Edition, Moore, Notz and Fligner, Freeman, 2018.

See bookstore website for current book(s) at https://www.dacc.edu/bookstore

EVALUATION:

The student shall be evaluated on the basis of quizzes & homework (15%), Excel lab projects* (7%), major examinations (60 %), final examination (18%), and progress during the course.

90-100%
80-89%
70-79%
60-69%
Below 60%
A
B
C
D
F

*A minimum of 6 Excel projects will be chosen from the following:
WEEKLY LAB OUTLINE: Labs are designed to develop students’ critical thinking skills and give them hands-on practice at applying the concepts discussed in class, organizing and analyzing data, and drawing and writing conclusions. Excel software will be used.
  • Lab 1 – Intro & Bar Graphs/Pie Charts:
    • Students are given a brief introduction to lab policies and procedures and create a bar graph/pie chart from given data.
  • Lab 2 – Histograms:
    • Students create a histogram from a given distribution and use the graph to describe the shape, center and spread of the distribution.
  • Lab 3 – Time Plots:
    • Students make a time plot from data and use it to describe cycles and trends.
  • Lab 4 – Measures of Center and Spread:
    • Students calculate several statistics and use multiple graphs to do individual and comparison analysis on two or more distributions.
  • Lab 5 – Standard Normal Curve Calculations:
    • Students create a template for performing various calculations involving the standard normal curve.
  • Lab 6 – Scatterplots, Regression and Correlation:
    • Students use given data to create a scatterplot and perform multivariate analysis using regression and the correlation coefficient.
  • Lab 7 – Residual Plots:
    • Students perform further multivariate analysis with the use of a residual plot they create.
  • Lab 8 – Probability Distributions:
    • Students make discrete probability distributions and calculate probabilities for simple random experiments, such as the outcome of the roll of two dice.
  • Lab 9 – Law of Large Numbers:
    • Students make an inference and test it by performing an experiment a “large” number of times, making calculations and graphing the results.
  • Lab 10 – Sampling Distributions of the Sample Mean:
    • Students consider continuous distributions by forming multiple random samples, calculating their sample means and creating a distribution of those sample means.
  • Lab 11 – Central Limit Theorem:
    • Students make further discoveries of the result of a sampling distribution, which leads to the Central Limit Theorem.
  • Lab 12 – One-Sample z Confidence Intervals
  • Lab 13 – One-Sample z Significance Tests
  • Lab 14 – One-Sample t Confidence Intervals
  • Lab 15 – One-Sample t Significance Tests

BIBLIOGRAPHY:

Current internet resources.

STUDENT CONDUCT CODE:
Membership in the DACC community brings both rights and responsibility. As a student at DACC, you are expected to exhibit conduct compatible with the educational mission of the College. Academic dishonesty, including but not limited to, cheating and plagiarism, is not tolerated. A DACC student is also required to abide by the acceptable use policies of copyright and peer-to-peer file sharing. It is the student’s responsibility to become familiar with and adhere to the Student Code of Conduct as contained in the DACC Student Handbook. The Student Handbook is available in the Information Office in Vermilion Hall and online at: https://www.dacc.edu/student-handbook

DISABILITY SERVICES:
Any student who feels s/he may need an accommodation based on the impact of a disability should contact the Testing & Academic Services Center at 217-443-8708 (TTY 217-443-8701) or stop by Cannon Hall Room 103. Please speak with your instructor privately to discuss your specific accommodation needs in this course.

REVISION:
Fall 2019

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