Student Guide for Students in Mathematics/Psychology 42

Statistics for Behavioral Sciences

Hester-Haynes_Math 42-65110 and Psy 42-65210 Fall 2018

 

Instructor Information:

Instructor Information

Instructor: Ms. Juanita Hester-Haynes	Email: Inbox in Canvas or juanita.hester-haynes@fresnocitycollege.edu
Office:T110B	Phone: (559) 442-8200 Ext 8702
Class Time: TTH 1000-1150	Class Location: OAB-274
Office Hours: MW 13:30-14:30; W 9:30-11:30; F 9:00 - 10:00 am in T110B

Save Date!

• Add class: Aug 31, 2018 is the last day to add this class. No students will be added after this date.
• Withdrawal: Aug 31, 2018 is the last day to drop without a “W” and October 12, 2018 is the last to drop with a “W”.
• Holidays: Sept 3, Nov 12, Nov 22 and Nov 23, 2018.
• Final: The final is scheduled Tuesday December 11, 2018 at 1000 until 1150 in OAB-274.

Course Description:

Descriptive statistics, sampling, hypothesis testing, estimation, selected non-parametric techniques, ANOVA, and regression, with applications from psychology, biology, and social sciences. This course is designed for psychology majors and UC transfers. (4 units, 4 lecture hours)

Prerequisite: Math 103 or equivalent. Advisory: Eligibility for English 1A recommended.

Student Learning Outcomes:

• Students will be able to discuss the advantages and disadvantages of various research designs and sampling strategies.
• Students will calculate descriptive statistics for data sets including measures of central tendency, measures of dispersion, and measures of position.
• Students will determine point and interval estimates for the population parameter for one and two sample differences.
• Students will formulate hypotheses and conducts tests of significance for one and two sample difference using both the classical and p-value methods.
• Students will determine the effect size and power of a hypothesis test and, combining these with the corresponding confidence interval and hypothesis test conclusion, analyze the results of a study.
• Students will perform tests of significance using single-factor ANOVA techniques, including between-measures and within-measures designs, and two-way ANOVA techniques.

Student Learning Objectives:

Upon successful completion of the course, the student will be able to:

• Discuss the advantages and disadvantages of various research designs and sampling strategies.
• Distinguish among different scales of measurement and their implication on the research design.
• Graphically present data and interpret the displays.
• Calculate descriptive statistics for data sets including measures of central tendency, measures of dispersion, and measures of position.
• Apply the concepts of sample space and probability to solve problems with simple, compound, and conditional events.
• Describe probability distributions and calculate probabilities including the binomial, normal, Student’s t, and Chi-square distributions.
• Explain the role of the Central Limit Theorem in sample variability and error.
• Calculate point estimates and confidence intervals for the population parameters for one sample and for two sample differences.
• Determine and interpret the importance of Type I and Type II errors, level of statistical significance, and power in hypothesis testing.
• Select the appropriate statistical technique for testing a hypothesis and interpret the result.
• Formulate hypotheses and conduct tests of significance for one sample with the z, t, Chi-square and F statistics using the classical and/or the p-value methods.
• Determine the effect size and the power for one sample hypothesis tests.
• Calculate the linear correlation coefficient (r), the coefficient of determination, and the linear regression equation for bivariate data and explain the significance of each.
• Perform tests of significance using single-factor analysis of variance techniques including both between-sample and within-sample designs.
• Perform two-way analysis of variance.
• Perform a variety of nonparametric tests such as the Mann-Whitney U Test and the Spearman’s Rank Correlation Test.
• Interpret the output of computer based statistical software packages such as SPSS, SAS, EXCEL, Minicab or graphing calculators.
• Use the appropriate statistical techniques to analyze and interpret applications based on data sets from disciplines including psychology, sociology, business, education, and the natural, social, and health sciences.

Required Materials:

Textbook:

Great news: your textbook for this class is available for free online!

Statistics from OpenStax, ISBN 1-947172-05-0

You have several options to obtain this book:

• View online (Links to an external site.)
• Download a PDF (Links to an external site.)
• Download on iBooks (Links to an external site.)

You can use whichever formats you want. Web view is recommended -- the responsive design works seamlessly on any device.

Miscellaneous:

TI-83 or TI-84 graphing calculator or 4 AAA batteries if borrowing calculator during class lecture, pencils, stapler and computer or tablet to access canvas.

Class Policy:

Class Participation and Attendance:

I expect your presence and participation in class during lectures, discussions, and activities. Attendance is important for two reasons. The first important reason is the acquiring of useful information to prepare you for the exams. Students who do not sign the attendance sheet on the day of attendance will be counted absent. You don't need to tell me the reason for your absence; I assume if you are missing class it is for a good reason. I don't distinguish between excused or unexcused absences because if you miss class, you will miss discussion, my commentary on the text, homework, and more. In a short time, you'll will find yourself behind and impossible to catch up.

Secondly, you make the class interesting by asking questions and sharing your knowledge of key concepts. This class is a community of learning and all of us can contribute to the class to make it enjoyable.

 

Finally, the attendance policy is not to punish you. If you are faced with illness or emergency, please let me know right away, and the same applies if you want questions answered or additional help. I check my email in Canvas once a day and you can always come to my office hours.

Drop Policy:

If you do not attend class on the first day of class and do not participate in the first survey activity in canvas, then I drop you from the class. Before the drop date (Aug 31st w/o “W” or Oct 12th with “W”), I will drop you if you miss more than three days of face-to-face class meetings. Four tardies (or leaving early) less than ten minutes each is equivalent to ½ day absence. Missing more than 10 minutes in any hour will result in a ½ day absence.

Add Policy:

Students on the waitlist must attend the first class meeting to obtain instructor permission to add the class, as long as there is availability on the class roster to add.

Communication:

We will use Canvas, our learning management system, regularly for communication. Canvas is like a website for the class. You can access it from FCC website. You will want to select the "My Courses" tab and click on the link for our class. You will communicate with me through the inbox. I will respond within 24 hours on Mondays through Fridays. I teach more than one class so type your name and class so I am able to respond appropriately. Make sure to include a short subject line that summaries purpose of email and you may address me as Haynes, professor or Ms. H.

Classroom Etiquette:

Common courtesy rules apply in the classroom:

• Please respect your fellow classmates by conversing during content discussions only.
• Listening to the speaker during whole class discussions and group discussions.
• Take care of personal calls and texts outside of classroom.
• You are awake and speaking to peers about content while in groups.
• If you are late, come in quietly and with as little disruption as possible.
• Visitor or guest to class needs to be pre-approved by me. If not followed, then I may ask you to leave resulting as a class absence

Grading Overview:

Grading

Weight of Grades		Grading Scale
Seven Exam and Final	75%	A	100-90%
Seven Homework Assignments	15%	B	89-80%
Lecture Practice and Weekly Survey Assignments	10%	C	79-70%
		D	69-60%
Total	100%	F	59% - below

Lecture Practice and Weekly Survey Questions (10%):

The lecture practice questions are a tool to access your knowledge of the newly acquired skills from key concepts from the lecture. Students are allowed to collaborate and explain in small groups to complete the questions. These questions are completed in Canvas each week except exam week. On the first day, the survey question assignment must be completed, so I can gain invaluable information about your learning needs. Each completed survey is worth 10 points; otherwise, 0 points is earned by due date.

Homework (15%):

The seven assignments will be made and be due on dates shown on the tentative schedule. I will not accept any late assignments after the assignment’s due date.  Assignments turned in before or on the due date will receive twenty points if the following is adhered:

• The “Turn IN “date of the assignment as shown on the assignment sheet must appear on the paper along with name and class. (2 pts)
• Homework sheets must be arranged in the order shown on the assignment sheet and stapled in the upper left hand corner of the first page. (1 pts)
• ALL STEPS (as presented in class and in notes) must be shown and be readable by me.
• I will select four puzzles randomly from the assignment to grade on a 1 - 4 rubric scale based on the work shown. (16 pts)
• All puzzles completed (1 pts)

The assignment is accepted only in person before on the date it is due in order to receive points. I do not provide opportunities for extra credit assignments. I have the belief that all of you are capable of obtaining a passing grade.

Exams (75%):

Since I do drop one of the six exams (100 pts each), there are no makeups. The final is a cumulative exam and is not dropped. The final is worth two exams (200 pts). In order to take the exams, you may use TI-84 or 83, but for the first exam a scientific calculator is only allowed. The Final is scheduled on Dec 11 at 10:00 until 1150 in OAB-274.

Academic Policy:

Accommodations for students with disabilities: 

If you have a verified need for an academic accommodation or materials in alternate media (i.e. Braille, large print, electronic text, etc.) per the Americans with Disabilities Act (ADA) or Section 504 of the Rehabilitation Act, please contact me as soon as possible. If you think you have a learning disability but have not had it verified, Disabled Students Programs and Services (DSP&S) might be able to assist you. All information will be kept confidential.

Military Students

If you are a military student with the potential of being called to duty or training during the course of the semester, please contact your instructor no later than the first week of class.

FCC Policy on Incomplete Grades:

Fresno City College has written a policy that describes the policy for students to request a grade of incomplete (I) in a course “if all of the following conditions are met:

• The student has completed all but a minimal amount of the course work required for a final semester grade.
The student has a serious and verifiable reason for not completing the assigned course work.
• The student has a passing grade at the time the incomplete is granted.”
If you like to gain more information about the policy, refer to the Fresno City College Catalog in the academic requirement section.

FCC Policy on Academic Dishonesty

 Fresno City College has written a policy that describes the policy of academic dishonesty that is unacceptable in terms of cheating and plagiarism.

Cheating

It is the act of deception by which a student misleadingly demonstrates that he/she has mastered information on an academic exercise. Examples include but are not limited to:

• Copying or allowing another to copy a test, paper, project, or performance.
• Using unauthorized materials during a test, for example, notes, formula lists or “cheat sheets.”

• Taking a test for someone else or permitting someone to take a test for you.

Plagiarism

It is the act of representing the work of another as one’s own without giving credit. Plagiarism includes but is not limited to:

• Incorporating the ideas or words of another’s work without giving appropriate credit.
• Representing another’s artistic or scholarly works, such as musical compositions, computer programs, photographs, etc., as one’s own.” (See the Fresno City College Catalog in the administrative requirement section)

Disciplinary Procedures

When a faculty member discovers a violation of the cheating or plagiarism policy, the faculty member:

• Will arrange a conference with the student and at that time advise the student of the allegations.
• Will notify the dean of the division in writing that an act of dishonesty has occurred. This report will become a part of the student's permanent record. A copy will be mailed or given to the student.
• May give the student an "F" for the assignment and/or for the course, depending upon the seriousness of the infraction.

If the student's permanent record indicates more than one occurrence of cheating or plagiarism, the student may be placed on probation, suspended or expelled by the Dean of Students. A student may appeal to the Academic Standards Committee any sanctions employed based on an allegation of dishonesty. Such an appeal must be made within fifteen (15) days after notification is mailed or given to the student.

Final Note

I chose the career of a mathematics instructor because I want to make a difference by helping students to understand difficult mathematical concepts so, please ask if you need help. Always remember, how you arrive at an answer is more important than the actual answer.

 

Tentative Course Outline:

Tentative Course Outline

Date	Assignments	Topic
Aug 13- 28		Section 1: ●     Sampling and Data ●     Frequency Tables ●     Research and Design
Aug 16	Canvas Survey (10 pts)	About Me and Grit
Aug 23	Lecture Survey (10 pts)
Aug 28	Homework Assignment 1 Due (20 pts)	Section 1 Exam (100 pts)
Aug 31		Drop without “W”
Sept 3		Holiday
Aug 29-Sept 11		Section 2: ●     Graphs ●     Central Tendencies ●     Variability
Sept 6	Lecture Survey (10 pts)
Sept 11	Homework Assignment  2 Due (20 pts)	Section 2 Exam (100 pts)
Sept 12-Sept 25		Section 3: ●         Basic Probability ●         Discrete Probability
Sept 20	Lecture Survey (10 pts)
Sept 24-25	Homework Assignment  3 Due (20 pts)	Section 3 Exam (100 pts)
Sept 26-Oct 11		Section 4: ●         Continuous Probability ●         Normal Distribution ●         Central Limit Theorem
Oct 4	Lecture Survey (10 pts)
Oct 12		Drop with “W”
Oct 11	Homework Assignment 4 Due (20 points)	Section 4 Exam (100 pts)
Oct 15 - Oct 30		Section 5: ●         Point Estimates and Confidence Intervals ●         Hypothesis Testing for Single Sample ●         Type I & II Errors, Effect Size and Power
Oct 18	Lecture Survey ( 10 pts)
Oct 25	Lecture Survey (10 pts)
Oct 30	Homework Assignment 5 Due (20 points)	Section 5 Exam (100 pts)
Oct 31-Nov 15		Section 6: ●         Hypothesis Testing for Two Sample ●         One-Way and Two Way ANOVA
Nov 8	Lecture Survey (10 pts)
Nov 12		Veterans Holiday
Nov 15	Homework Assignment 6 Due (20 points)	Section 6 Exam (100 pts)
Nov 19- Dec 4		Section 7: ●         Correlation ●         Linear Regression. ●         Non-Parametric Test
Nov 20	Lecture Survey (10 pts)
Nov 22-23		Thanksgiving Break
Nov 29	Lecture Survey (10 pts)
Dec 4	Homework Assignment 6 Due (20 points)	Section 6 Exam (100 pts)
Dec 6		Review for Final
Dec 11	10:00-11:50 pm	Cumulative Final (200 points)

 

Tentative Schedule for Assignments

 

Tentative Schedule for Assignments

Section Date	Read Pages/Chapter Section	Lecture Practice	Homework
Section 1: Aug 13- 28	Pg 5-38/Ch1.1-1.4	Chapter 1: Pg 49: #11, 12-15, 43, 45, 47, 50-52, 58, 65, 68, 73, 82, 87, 88.	Chapter 1: Pg 52: #42, 44, 46, 49, 54, 55, 60, 66, 72, 75, 81, 84.
Section 2 Aug 29-Sept 11	Pg 68-172/ Ch 2.1-2.7	Chapter 2: Pg 127:#1, 5, 8, 18b, 21a, b, 23, 24, 25, 40-45, 49-55, 73a.	Chapter 2: Pg 140: #74, 76, 81, 84, 90, 92, 113, 114, 118a-i, 120.
Section 3 Sept 12-25	Pg 172-195/Ch 3.1-3.4   Pg 240-257/Ch 4.1-4.3	Chapter 3 and 4: Pg 213: #1-5, 37-39, 83, 85, 86, 89, 101-106, 113, 144, 115.   Pg 280:# 1-9, 18, 20, 37-43, 76, 92, 95.	Chapter 3 and 4: Pg 213: #6-10, 82, 88, 99, 112.   Pg 280:# 23-27,78a-d, 76, 88, 100.
Section 4 Sept 26- Oct 11	Pg 309-321/Ch 5.1-5.2   Pg 363-374/Ch 6.1-6.2   Pg 396-413/Ch 7.1-7.3	Chapter 5, 6 and 7: Pg 341: #1-4, 12, 75, 77   Pg 381: #1-3, 11, 13, 15, 17, 20, 23, 27, 35, 37, 48, 51, 53, 55, 64, 75, 78, 80, 87.   Pg 422: #1-4, 7-10, 16-18, 31, 62, 70.	Chapter 5, 6 and 7: Pg 341: #14, 74.   Pg 381: # 18, 22, 30, 50, 52, 54, 60-61, 66, 74.   Pg 424:#11-14, 32, 64,
Section 5 Oct 12- Oct 30	Pg 441-462/Ch 8.1-8.3   Pg 502-527/Ch 9.1-9.5   Handout for effect size	Chapter 8 and 9: Pg 473; #1, 9, 43, 47, 64, 67, 95, 97, 106, 121, 125-127.   Pg 535; #9, 11, 15, 68, 69, 101, 103, 105, 115.	Chapter 8 and 9:: Pg 473; #6, 13, 18, 38, 81, 85. 96, 98, 105, 120   Pg 535; #8, 12, 100, 102, 104, 112, 114   Handout for effect size
Section 6: Oct 31- Nov 15	Pg 562-583/Ch 10.1-10.4   Pg 738-753/Ch 13.1-13.4   Handout for Two- Way ANOVA	Chapter 10  and 13: Pg 590: #1, 3, 5, 31-35, 46-50, 63-66, 73-77   Pg  764; #6-15, 33-39, 52-58.	Chapter 10 and 13: Pg 590: 2, 4, 6, 36-40, 80, 82, 94, 96,107, 109, 115, 123.   Pg 769; # 64, 65, 69, 76, 80.     Two-Way ANOVA  Handout
Section 7: Nov 16-Dec 4	Pg 616-636/Ch 11.1-11.6   Pg 674-699/Ch 12.1-12.6	Chapter 11 and 12: Pg 654; #14-21, 75, 77, 123.   Pg 712; #1, 2, 3, 12-14, 17-19, 20-24, 31-32, 37-38, 51-52.	Chapter 11 and 12: Pg 654; #72, 74, 78, 122, 124.   Pg719; #57, 38, 60, 68, 73,