**Course Lecturer Name(s): **Dr. Curlan Gilchrist** **

**Course Lecturer(s) Contact Information: (473) 444-4175 ext. 3255 cgilchrist@sgu.edu**

**Course Director Contact Information: **

**Course Lecturer(s) Office Hours: **Mon, 10:00am –11:00 am** **

**Course Lecturer(s) Office Location: Caribbean House/Zoom meeting**

**Course Support: **Mary Celestine, MCelesti@sgu.edu

**Course Management tool: **To learn to use Sakai, the Course management tool, access the link https://apps.sgu.edu/members.nsf/mycoursesintro.pdf

**Course Description: **

The course is designed to assist the student in acquiring a good intuitive grasp of statistics, specifically in terms of what it is, how and when to apply various statistical methods, how to interpret the results and draw meaningful conclusions from the data. The course gives introduction to concepts in probability, basic statistical inference procedures of estimation, confidence intervals and hypothesis testing.

**Course Objectives:**

- Summarize data graphically by displaying data using methods from descriptive statistics;
- Interpreting data in tables graphically by using histograms, frequency distributions, box-and whisker (five-number summary);
- Find measures of central tendency for data sets: mean, median, and mode; find measures of variation for data sets: standard deviation, variance, and range; relative positions of data and distinguish among scales of measurements and their implications; distinguish between populations and samples; and identify the standard method of obtaining data and the advantages and disadvantages of each.
- Standardize a normally distributed random variable, use normal distribution tables to find probabilities for normally distributed random variables and the t-distribution, and use the Central Limit Theorem to find probabilities for sampling distributions.
- Construct and interpret confidence intervals for proportions and means.
- Identify the basics of hypothesis testing and perform hypothesis testing for means, proportions and standard deviations from one population, and difference of means and proportions from two populations, including finding and interpreting p-value and examining Type I and Type II error.
- Find linear least-squares regression equations for appropriate data sets, graph least-square regression equations on the scatter plot for the data sets, and find and apply the coefficient of correlation.
- Use the chi-square distribution to test independence and to test goodness of fit.

**Student Learning Outcomes: **

Upon completion of this course, students will be able to:

- Identify the similarities and differences between the various measures of central tendency
- Use the frequency distribution to compute the various measures of central tendency
- Compute the various measures of variations and explain their usefulness
- Construct and interpret stem-and-leaf plot
- Construct and interpret a dot plot
- Define key concepts (probability, event, sample space, experiment)
- Explain the classical and relative frequency approaches to probability
- Explain the addition rules and the concept of mutual exclusive
- Explain the multiplication rule and the concept of independence
- Explain marginal and conditional probability
- Define random variables
- Compute the expected value, variance, and standard deviation of random variables
- Calculate probabilities using the binomial and Poisson formulae
- Explain the features of the normal distribution; find probabilities using the normal distribution table
- Explain the features of the t-distribution; find probabilities using the t-table
- Explain the main elements of the central limit theorem
- Determine point estimates for population mean, standard deviation and proportion
- Determine interval estimates for population mean and proportion where the population standard deviation is either known or unknown
- Determine the critical values associated with 90% ,95%, and 99% degree of confidence
- Define a hypothesis test; explain the type of errors, the type of test 21. Define the significant level of the test, the power of the test

- Explain the steps in carrying out a test using the traditional method
- Explain the steps in carrying out a test using the p-value
- Construct a one tail or two tail test about a population mean, population proportion
- Compute and interpret the correlation coefficient, r
- Compute the constant and slope coefficient of the regression equation
- Explain the features of a contingency table
- Explain the features of the chi square distribution
- Use the chi square statistic to carry out a test of independence

**Program Outcomes Met By This Course: **

N/A** **

**SAS Grading Scale:** Grades will be assigned as follows:

A = 89.5% or better

B+ = 84.5 - 89.4%

B = 79.5 - 84.4%

C+ = 74.5 - 79.4%

C = 69.5 - 74.4%

D = 64.5 - 69.4%

F = 64.4% or less

**Course Materials: **

*Text:* Mario F. Triola, “Elementary Statistics”

**Course Grading Requirement: **

- Midterm exam: 25%
- Final exam: 25%
- Assignments: 10%
- Quizzes: 20%
- Labs: 15%
- Class participation and attendance 5%

**Course Requirements: **

Students will be required to:

- be prepared for class: look pre-recorded lectures in Panopto before the class, read corresponding chapters in the textbook;
- contribute thoughtful ideas to class discussions;
- conduct themselves in an appropriate manner, including being respectful of the opinions of others; - listen carefully to instructions given by lecturer; if you do not understand, ask the lecturer.

**Course Schedule**:

**Week 1 & 2 – **

**Introduction to Course****Measures of central tendency (mean, mode, median, trimmed mean, weighted mean, harmonic mean, geometric mean)****Frequency distribution ( grouped or ungrouped data)****Measures of variation (range, standard deviation, empirical rule, coefficient of variation,****Measures of relative standing (z score, quartiles, percentiles)**

**Week 3 – **

**Charts, Graphs (histogram, bar chart, pie chart, dot plot, stem-and-leaf-plot, scatter plot, time-series graph,**

**Week 4 – **

**Probability and Probability Distribution Fundamentals****Addition rule ( mutually exclusive)****Multiplication rule (independence, conditional)**

**Week 5 – **

**Probability and Probability Distribution****Random variables****Permutation and Combination****Binomial distribution****Poisson distribution**

**Week 6 – **

**Probability and Probability Distribution****Normal Probability Distributions****T-distribution****Estimates and Sample Sizes****Sampling and Sampling distribution****Central limit theorem**

**Week 7 – **

**Midterm Review**

**Week 8 – **

**- Midterm Examination**

**Week 9 – **

**Estimates from samples****Estimating population mean****Estimating population proportion**

**Week 10 – **

**Hypothesis Testing****Testing a claim about a mean**

**Week 11 – **

**Hypothesis Testing****Testing a claim about a population mean****Testing a claim about a population proportion**

**Week 12 – **

**Correlation and Regression**

**Week 13 – **

**Regression****Contingency Tables****Test of independence**

**Week 14 – **

**Contingency Tables****Test of independence**

**Week 15 – **** **

**Review**

**Week 16 – **

**Final Examination**

## School of Arts and Sciences Master Syllabi — Info for All Sections

**Academic Integrity**

*The St. George’s University Student Manual (2019/2020)* states as follows:

“*Plagiarism is regarded as a cardinal offense in academia because it constitutes theft of the work of someone else, which is then purported as the original work of the plagiarist. Plagiarism draws into disrepute the credibility of the Institution, its faculty, and students; therefore, it is not tolerated*” (p. 48).

Plagiarism also includes the unintentional copying or false accreditation of work, so double check your assignments **BEFORE** you hand them in.

Be sure to do good, honest work, credit your sources and reference accordingly and adhere to the University’s Honor Code. Plagiarism and cheating will be dealt with very seriously following the university’s policies on Plagiarism as outlined in the Student Manual.

Your work may be subject to submission to plagiarism detection software, submission to this system means that your work automatically becomes part of that database and can be compared with the work of your classmates.

*The St. George’s University Student Manual (2019/2020)* states as follows:

“*Students are expected to attend all classes and or clinical rotations for which they have registered. Although attendance may not be recorded at every academic activity, attendance may be taken randomly. Students’ absence may adversely affect their academic status as specified in the grading policy. If absence from individual classes, examinations, and activities, or from the University itself is anticipated, or occurs spontaneously due to illness or other extenuating circumstances, proper notification procedures must be followed. A particular course may define additional policies regarding specific attendance or participation*” (p. 9).

*The St. George’s University Student Manual (2019/2020)* states as follows:

“*All matriculated students are expected to attend all assigned academic activities for each course currently registered. Medical excuses will be based on self-reporting by students. Students who feel they are too sick to take an examination or other required activity on a specific day must submit the online SAS medical excuse, which is available on Carenage. Students are only allowed two such excuses a year. Upon consultation with the Director of University Health Service, the third excuse will result in a mandatory medical leave of absence. The policies regarding make-up examinations are at the option of the Course Director*” (p.46).

For additional specific examination policies and procedures, refer to the St. George’s University Student Manual (2019/2020), pages 31 through 37.

*The St. George’s University Student Manual (2019/2020)* states as follows:

“*A student with a disability or disabling condition that affects one or more major life activities, who would like to request an accommodation, must submit a completed application form and supporting documentation to the Student Accessibility and Accommodation Services (SAAS) located in the Dean of Students Office. It is highly recommended that students applying for accommodations do so at least one month before classes begin to allow for a more efficient and timely consideration of the request. If a fully completed application is not submitted in a timely fashion, an eligibility determination may not be made, and accommodations, where applicable, may not be granted prior to the commencement of classes and/or examinations*” (p. 8).

It is the responsibility of the student to read and understand the policies, laws, rules and procedures that while they could affect your grade for a course, have not been specifically outlined in the course syllabus. These are contained in the *St. George’s University Student Manual*.