STAT 101 –  Statistics for Social Sciences 

Spring 2023

The general information provided in the Modules tool is a supplement to the course syllabus. Please make sure to read that information as well as the information contained in the syllabus. 

Professor: Ali Ghassemi, PsyD

Email: ghassear@lavc.edu

Office Phone: 818.947.2522 (please communicate and ask questions via email, and Inbox messaging. If you leave a voice mail, please send me a message via inbox as I am on campus only two days per week) 

Office: Online Monday-Friday via Canvas Inbox 8am - 6pm

Course Description and Information

This course will introduce you to mathematical techniques commonly used by researchers to organize, summarize and analyze data.  You will be shown how to compute statistical tests using simple data sets.  Skills that you will begin to develop in this course include critical thinking, analyzing data using SPSS, understanding the rationale behind various statistical procedures as well as gaining an understanding of the appropriate uses of various statistical methods.  

Course Textbook (required) 

• Salkind, N. J. & Frey, B. B. (2020) Statistics for people who (think they) hate statistics 7^th Edition, Sage Publications (ISBN-978-1-5063-3383-0). 
  • Note: You may use the 5^th, 6^th, 7^th edition of the textbook and can use a hardcopy or ecopy.  

Student Learning Outcome: Upon successful completion of this course, you will be able to evaluate and interpret data using statistical concepts. 

Course Materials and Required Technology 

• Calculator capable of performing basic mathematical operations such as square root. You will be responsible for becoming familiar with the operation of the calculator.  You might want to consider purchasing T1-34 Calculator. 
• You will be expected to complete weekly quizzes, and assignments. 
• You will need regular access to a computer with a connection to the Internet. 
• You will also need access to the following software:  
• Adobe Acrobat Reader ^© to open PDF files that are used during the course. 
• Internet browser that is compatible with Canvas online learning environments. 
• You will also need access to a scanner, which could be a free or low-cost smartphone app. If you do not have a smartphone or access to a scanner, please let me know.   
• You will need to have access to The Microsoft Office suite of software. Other programs that allow you to open and save Microsoft office files (including Word, PowerPoint, and Excel) is also acceptable. The following link will explain how you can get a copy of Microsoft Office:   https://www.lavc.edu/getconnected/email-onedrive.aspx 

Course Objectives

• Students will be able to evaluate and interpret data using statistical concepts. 
• Students can recognize and define basic descriptive and inferential statistical terms and concepts. 
• Students can demonstrate competence in using SPSS for data manipulations and analysis. 
• Students can recognize when and when not to use certain statistical procedures. 
• Students can apply statistical procedures to data in order to answer research questions. 

 Central Course Topics (not exhaustive, and not in the order presented in class):

Introductory Concepts 

•   Distinguish between a population and a sample. 

•   Distinguish between a parameter and a statistic. 

•   Distinguish between the purposes of descriptive statistics and inferential statistics. 

•   Describe the methods, benefits, and limitations of probability sampling strategies. 

•   Compare nominal, ordinal, interval, and ratio scales of measurement. 

  

Frequency Distributions 

•   Construct a distribution of class intervals from a given data set. 

•   Determine the midpoint, upper class limit, and lower class limit of a given class interval. 

•   Compare histograms, bar graphs, and frequency polygons in terms of their function and characteristics. 

•   Construct a frequency table, histogram, bar graph, and frequency polygon from a given data set. 

•   Describe the symmetry of a distribution or data set. 

•   Determine whether a given data set represents a leptokurtic, mesokurtic, or platykurtic distribution. 

  

Central Tendency and Variability 

•   Compare measures of central tendency in terms of their meaning and limitations. 

•   Calculate the mean, median, and mode of a given data set. 

•   Explain the meaning of a multimodal distribution. 

•   Determine the impact of changing values in a given data set on the mean, median, and mode. 

•   Describe how measures of central tendency and measures of variability complement one another. 

•   Compare measures of variability in terms of their meaning and limitations. 

•   Calculate the range, variance, and standard deviation of a given data set. 

•   Determine the most appropriate measure for reporting the central tendency and variability of a given data set. 

  

Normal Curve and Inferential Statistics 

•   Describe the properties of the normal distribution. 

•   Compare two scores from given distributions and interpret the results. 

•   Explain the purpose of using standardized scores. 

•   Convert raw scores to standardized scores and vice versa based on a given set of data. 

•   Explain the practical significance of a standardized distribution. 

•   Determine the proportion of scores within a given standard deviation in a standardized distribution. 

•   Compare percentile ranks and percentiles. 

•   Interpret a percentile based on a raw score and normal distribution. 

•   Explain the relationship between probability and inferential statistics. 

  

Hypothesis Testing 

•   Explain what a sampling distribution represents. 

•   Formulate a null, alternative, directional, and non-directional hypothesis for a specified test. 

•   Explain the relationship between probability and hypothesis testing. 

•   Explain the practical significance of Type I and Type II error and the procedures used to minimize them. 

•   Test a statistical hypothesis, and interpret the results. 

•   Determine whether a one- or two-tailed test is more appropriate for evaluating a specific situation. 

•   Explain the implications of the relationship between alpha level, power, and Type I and Type II error for research design and hypothesis testing. 

  

Correlation  

•   Explain the purpose of evaluating a correlation. 

•   Describe the relationship between two variables based on their distributions. 

•   Calculate Pearson's correlation coefficient for a given data set and interpret the results. 

•   Explain the assumptions that should be checked when calculating Pearson's correlation coefficient. 

•   Explain the relationship between correlation and causation. 

•   Describe how restricted ranges and outliers affect correlation coefficients. 

•   Explain the relationship between the correlation coefficient and the coefficient of determination. 

 

Regression 

•   Describe the relationship between correlation analyses and regression analyses. 

•   Determine the equation for the regression line for a given data set or correlation coefficient. 

•   Conduct a regression test and interpret the results. 

•   Explain what a standard error of the estimate means in terms of regression. 

•   Determine the proportion of variance accounted for by a set of variables. 

  

T-tests 

•   Describe the differences between an independent-samples t-test and a dependent-sample t-test. 

•   Conduct a t-test to compare two independent groups and interpret the results. 

•   Explain the assumptions that should be checked when conducting an independent-samples t-test. 

•   Conduct a t-test for two dependent samples and interpret the results. 

•   Explain the assumptions that should be checked when conducting a dependent-samples t-test. 

  

ANOVA 

•   Determine whether a t-test or ANOVA is more appropriate in a given situation. 

•   Conduct an ANOVA and interpret the results. 

•   Compare between-groups and within-groups variance. 

•   Explain the assumptions that should be checked when conducting a dependent-samples t-test to the extent that they are relevant to ANOVA. 

•   Explain the considerations for sample size when conducting an ANOVA. 

•   Calculated the values needed to construct an ANOVA summary table. 

•   Explain the purpose and considerations for conducting post hoc ANOVA comparisons. 

  

Chi-Square 

•   Compare parametric and nonparametric statistical tests. 

•   Conduct a chi square goodness-of-fit test and interpret the results. 

  

Course Requirements 

Quizzes (110 Points)  

There will be 13 quizzes, each worth 10 points. Quizzes will be multiple choice, but answers might require independent calculation on your part. Each quiz has 20 questions, each question is worth 0.5 point. I will only count your highest 11 quiz scores for your final grade (11 x 10 = 110). Weekly quizzes are untimed; however, once you log in to complete the quiz, you must complete it in one seating. If you log off before finishing your quiz, you will not be allowed back in. Some weeks the quiz will coincide with Comp Exams.  You will need a calculator with a square and square root function. Quizzes will require definitional, procedural, and applied knowledge wherein you will be asked to define and identify concepts, select appropriate techniques, complete hand-calculations, conduct and interpret analyses. A missed quiz will receive a score of zero, and could count as a quiz dropped if the total number of missed quizzes are no more than 2. If 3 or more quizzes are missed, the score of zero for each of them will count towards your final grade. Remember, there are no makeup quizzes/exams! 

Comprehensive Exams (300 Points) 

There will be 4 exams (100 points each). I will count your highest 3 exam scores (3 x 100 = 300) Concepts in statistics build upon each other so all previous information may be relevant on any exam even if it is not the focus of that exam. Comp Exams will have the same format as weekly quizzes, except that Comp Exams include more questions, and Comp Exams are timed. Each Comp Exam has a 85-minute time limit. A missed Comp Exam will receive a score of zero, and will count as the Comp Exam dropped if it is the only one missed for the semester. If 2 or more Comp Exams are missed, the score of zero for each of them will count towards your final grade. Remember, there are no makeup quizzes/exams!  

As with quizzes, you will need a calculator with a square and square root function. Exams will require definitional, procedural, and applied knowledge wherein you will be asked to define and identify concepts, select appropriate techniques, complete hand-calculations, conduct and interpret analyses. 

Homework (220 Points) 

There will be 13 homework assignments worth 20 points each. I will count your highest 11 homework scores (11 x 20 = 220 points). Homework assignments will vary and can include hand-calculations, analyses via software, interpretation, write-up, and other skills covered in the course and in the textbook. These assignments should serve as preparation for the exams by focusing your attention on where you need to study. You must submit weekly homework via Canvas, as a pdf file, or you can type in your answer in the editor. Late submissions, emailed submissions, or hard-copy versions will not be accepted for grading. A missed homework assignment will receive a score of zero, and it will count as the homework assignment dropped. If 3 or more homework assignments are missed, the score of zero for each of them will count towards your final grade. Please see below regarding Late Assignment/Missed exams.

Assignments (120 Points) 

There will be 6 assignments (likely related to SPSS) worth 20 points each (6 x 20 = 120). More details will be provided before each assignment is opened.

Final Exam (150 Points) 

The final exam will be similar in content to the midterm exams (multiple choice/working out problems). Final Exam opens on December 13. Final Exam is mandatory and it cannot be dropped. 

  

Course Schedule			Weekly Tasks
Week 1	Introduction & SPSS	Chp 1	Upload pdf
Week 2	Measures of Central Tendency	Chp 2	Homework 1  Quiz 1
Week 3	Variability	Chp 3	Homework 2  Quiz 2
Week 4	Frequency Distribution and Graphs	Chp 4	Homework 3  Quiz 3
Week 5	Hypothesis Testing	Chp 7	Homework 4  Quiz 4 Exam 1
Week 6	Normal Curve/Probability	Chp 8	Homework 5  Quiz 5 Assignment
Week 7	Significance	Chp 9	Homework 6  Assignment  Quiz 6
Week 8	Z-Test	Chp 10	Homework 7  Quiz 7 Exam 2
Week 9	T-test Independent Samples	Chp 11	Homework 8  Quiz 8
Week 10	T-test Dependent Samples	Chp 12	Homework 9  Quiz 9  Assignment
Week 11	ANOVA	Chp 13	Homework 10  Quiz 10 Exam 3
Week 12	Correlation/Correlation Testing	Chp 5, 15	Quiz 11 Homework 11 Assignment
Week 13	Regression	Chp 16	Homework 12  Quiz 12
Week 14	Chi Square	Chp 17	Homework 13 Quiz 13  Assignment
Week 15	Review/Catch Up		Exam 4

 

Grading: 

Final Grades for this class will be based on the following 

1. Upload a pdf: 5 points 
2. 11 Weekly Quizzes: 110 Points 
3. 3 Comprehensive Exams: 300 Points 
4. 11 Homework: 220 Points 
5. 6 SPSS Assignments: 120 Points 
6. Final Exam: 150 Points 

Total Points: 905 

815 – 905 Points = A 

724 – 814.5 = B 

633 – 723.5 = C 

540 – 632.5 = D 

539.5 and below = F 

 

IMPORTANT POLICIES AND NOTES:

Free Tutoring 

For detailed information call the tutoring center at 818-947-2744 or visit General Tutoring or email tutoring@lavc.edu. 

No Review Policy: Psychology Department at Los Angeles Valley College has adopted a 'No Review Policy' on tests and quizzes. Upon completion of a test or a quiz, there will not be any review of the answers so it is suggested that students take note of any areas that they found difficult.

No Late Submission of Exams/Quizzes/Assignments: Policies of Psychology Department prevent me from offering any makeup exams or from accepting any late assignments.

Policy on Academic Dishonesty: Los Angeles Valley College has an established academic dishonesty policy in accordance with the standards of student conduct. The policy is published in the college catalogue, and it is your responsibility to be familiar with its provisions. Academic dishonesty, including cheating will be immediately reported to the Department Chair and the necessary documentation submitted to the Vice President of Student Services, who will render appropriate disciplinary actions. You may find the policy at http://www.lavc.edu/policies/index.aspx#academicdishonesty (Links to an external site.).

Academic Integrity:  I expect that all work you turn in to me reflect your own efforts and ideas. Plagiarism, cheating, copying, bringing/using unauthorized material(s) during exams, or any form of academic dishonesty will not be tolerated in this course!  Plagiarism is a form of cheating which consists of using another person’s knowledge or ideas without giving credit to them.  Plagiarism can occur deliberately or unintentionally. However, plagiarism for any reason is a serious offense.  Consequences for any offense against academic honesty and integrity may include an F (zero) on the assignment or an F in the course. 

Students who are not officially enrolled will not receive credit for any exams or assignments, even if I have mistakenly graded assignments or exams. It is your responsibility to keep a record of your enrollment and confirm your class schedule. 

Exclusion from the class: This course requires active participation throughout the semester. Students who have not checked in with the course as of midnight on February 7 will be excluded from the course. If at any time during the semester you cannot attend class, you must notify me. If you I do not get any notification from you, and if you are inactive for any consecutive 14 days during the semester, or you have missed two consecutive tasks (quiz/exam/CT Part I/CT Part II), I reserve the right to exclude you from the class. Participation in the course involves active contribution in course discussion, taking the exams, posting questions regarding course content in the Question Forum, etc. Traveling out of town or lack of access to the internet (for any reason) is never an excuse. I will excuse inactivity only due to serious emergency, in which case you must present appropriate documentation to verify the situation. I may require you to submit your documentation to me in person at LAVC.

Withdrawing from the class: After I have completed exclusion of students who are "No Show" to class, it is your sole responsibility to withdraw from the class, if you decide to no longer attend. Please refer to the schedule of classes for withdrawal dates. You may also visit www.lavc.edu for specific dates. If you stop attending the class, but your name appears on the final grade roster, I am obligated to assign a grade to you, which in all likelihood would be an "F". Unless there are compelling reasons that are beyond control, I will not grant an "INC" to any student. For Example, having too many classes (units), excessive work and family responsibility, difficulty with transportation, travel (for any reason) are not considered grounds for an INC. Ultimately, I have the sole decision making authority in the matter.

Students who are not officially enrolled will not receive credit for any exams or assignments, even if I have mistakenly graded assignments or exams. It is your responsibility to keep a record of your enrollment and confirm your class schedule

Student Resources: Los Angeles Valley College has numerous services to help you succeed in your education. Here are some highlights. I highly recommend that you take full advantage of these services! Some of the services might only be available to you online. 

Services for Students with Disabilities 

If you are a student with a disability and require classroom accommodations, contact Services for Students with Disabilities (SSD) in a timely manner. SSD is located in Student Services Annex Room 175. For further information, contact SSD at (818) 947-2681 or (818) 947-2680 (TTY). If SSD has already sent a memo confirming accommodations, please meet with me to discuss arrangements. 

Associate Degree in Psychology for Transfer 

The psychology department now offers an Associate Degree in Psychology for transfer. See 

What does the Associate Degree for Transfer program do for me? 

Creates an Associate Degree for Transfer that guarantees your admission with junior standing to the California State University system. 

Defines this associate degree as having 60 transferable units that include a minimum of 18 units in a major or area of emphasis and an approved general education curriculum (either IGETC or GE Breadth). 

Provides you with priority admission consideration to your local California State University campus and to a program or major that is similar to the major or area of emphasis you studied at your community college. 

Prohibits the California State University from requiring you to repeat courses that are similar to those completed at your community college as part of your Associate Degree for Transfer. 

Prohibits the California State University from requiring you to take more than 60 units to complete a 120-unit baccalaureate degree.