Students are required to attend every lecture. Attendance will be taken. Students must email the Instructor to notify and account for any absences. 

There will be two exams given in the course, as well as a quiz.. 

Please review these policies and other issues:

Students should familiarize themselves with ACC policies, procedures, expectation, and the Student Handbook via www.austincc.edu.  The last day for a student to withdraw is listed at http://www.austincc.edu/calendars/academic-calendar. Students should review the information available at http://www.austincc.edu/current for information about withdrawals, deadlines, transcripts, financial aid, health issues, international student status, or academic standing. It is highly recommended that the student see an advisor or counselor before making changes to their enrollment status, such as a Drop.

For a student to make an A in the class, two hours of focused research on each class' topic is likely necessary at a minimum. Participation in class discussions is highly encouraged. It is better to ask questions than to wonder silently, and on-topic observations are welcomed. Challenging the professor is often appropriate, and may even be necessary. Attendance in the class is the way to get the most out of the course, as I will make a serious effort to make these topics come alive.

ACC expects our students to be mature, collegial, and responsible.  Naturally, any student whose conduct or dress at any time is in violation of the law, is a public nuisance, or is deemed improper or detrimental to the College may be subject to warnings and/or disciplinary action.  It is only fair that students are therefore expected to respect the rights and welfare of other members of the College community and its guests. As such, violence, the threat of violence, any disruption to the learning process, or intimidation will be subject to disciplinary action.

In keeping with the great tradition of free inquiry and the life of the mind so critical to higher education and Western Civilization, the Department of Psychology respects Academic Freedom. Therefore, each student is certainly strongly encouraged to participate in discussions. However, in any classroom situation that includes discussion and critical thinking about the mind, behavior, and the nature of human beings, there will be many differing viewpoints. This exposure is a strength, and not a weakness, as consideration of diverse views is critical for intellectual and professional development. It is to be expected that students may disagree with each other at times. Patient, thoughtful, respectful exchanges are the expected result of differences of opinion. Learning to disagree, and to have one’s ideas challenged, is interesting, stimulating, and of paramount importance to one’s career and to the life of the mind. The students and the instructor may also find that they have divergent views on sensitive and emotionally powerful themes.  These differences can certainly enhance the course experience!   Of course your grade will not be adversely affected by any beliefs or ideas expressed in class or assignments. On the contrary, it is expected that all of us do our best to respect the views of others, when expressed in classroom discussions. This includes respectful disagreement, debate, and welcoming ciritique. These are skills an adult should attempt to master, as they are vital to civic life, fulfliing as one develops intellectually, and of great value to industry and the economy.

Recommended text: Statistics for the Behavioral Sciences Second Edition. Susan A. Nolan | Thomas E. Heinzen. http://students.aiu.edu/submissions/profiles/resources/onlineBook/T9X7w6_Statistics_for_the_Behavioral_Sciences-_2.pdf

Overall, we will examine how to reason about and think critically about probability,  chance/randomness vs determinism, the laws of science, knowing whether we know or just think we know i.e epistemology, causality vs correlation, risk factors, hypothesis testing, prediction, statistical modeling, rare events, bias, statistical inference, what constitutes good scientific practices, false positive and false negatives, analytics and statistical software, machine learning and AI, the practical utility of statistical modeling for the modern organization, and why researchers makes mistakes with statistics, due to sampling error, bias, and professional pressure.

The GPT-powered Bing is a good resource: https://www.bing.com/ for questions like 'What is a p value"? Wikipedis also useful: https://en.wikipedia.org/wiki/Statistics

Week 1 Introduction: cognition, empiricism, science, statistics, and epistemology, : knowing whether we know or just think we know, truth. opinion, bias  https://www.youtube.com/watch?v=r_Y3utIeTPg and https://www.youtube.com/watch?v=6SQDD5E0jZA Epistemology from the Stanford Encyclopedia of Philosophy: https://plato.stanford.edu/entries/epistemology/

The scientific method: https://www.youtube.com/watch?v=SMGRe824kak and https://www.youtube.com/watch?v=yi0hwFDQTSQ

Bayes' theorem: what do we believe, and should we update our prior beliefs when new knowledge appears? https://www.youtube.com/watch?v=HZGCoVF3YvM and https://plato.stanford.edu/entries/bayes-theorem/

P values

The "replication crisis" in psychology and other fields: https://www.youtube.com/watch?v=42QuXLucH3Q and https://www.youtube.com/watch?v=vBzEGSm23y8

Week 2  (recommend Chapter 1 of Statistics for the Behavioral Sciences text)

The Two Branches of Statistics
Descriptive Statistics
Inferential Statistics
Distinguishing Between a Sample and a Population
Independent, Dependent, and Confounding Variables
Introduction to Hypothesis Testing

Week 3 (recommend Chapter 2 of Statistics for the Behavioral Sciences text)
Frequency Distributions
Shapes of Distributions
Normal vs Bimodal Distributions
Skewed Distributions: kurtosis

Frequency distrbutions: the shape of data from empirical measurements:https://www.youtube.com/watch?v=bPFNxD3Yg6U and https://www.youtube.com/watch?v=oI3hZJqXJuc]

Hypothesis testing: https://www.investopedia.com/terms/h/hypothesistesting.asp#:~:text=Hypothesis%20testing%20refers%20to%20a,hypothesis%20and%20the%20alternative%20hypothesis.

Week 4: Recommend Chapter 4 of Statistics for the Behavioral Sciences: Central Tendency and Variability

Measures of the central tendency: mean, median and mode: https://www.youtube.com/watch?v=AdH5vfobH5E and https://www.youtube.com/watch?v=kn83BA7cRNM

Sampling and Probability

Samples and Their Populations
The Problem with a Biased Sample
Probability
Coincidence and Probability

Inferential Statistics

Developing Hypotheses and Making a Decision About Our Hypothesis: reject or accept the Null hypothesis?

Type 1 and Type 2 Errors: false positives and false negatives, true positives and true negative results: https://www.youtube.com/watch?v=CJvmp2gx7DQ and https://www.youtube.com/watch?v=SBt7q2m_Ncw

The Normal Curve, Standardization, and z Scores

Bell curves/normal distribution: https://www.youtube.com/watch?v=rzFX5NWojp0
Need for Standardization: z Scores, and the Normal Curve
Law of Large Numbers and the Central Limit Theorem
Characteristics of the Distribution of Means

Recommend Chapter 7 of Statistics for the Behavioral Sciences:

Hypothesis Testing with z Tests and the z Table

Week 5 Review

Week 6 Review and Midterm

Week 7: Confidence Intervals, Effect Size, and Statistical Power

Confidence Intervals
Effect Size: Cohen’s d

Power & Effect Size https://www.youtube.com/watch?v=9LVD9oLg1A0

 Recommend Chapter 9, 10, 11 of Statistics for the Behavioral Sciences

What is ANOVA?  https://www.investopedia.com/terms/a/anova.asp

How to think about and perform basic linear regression on plotted data: https://www.youtube.com/watch?v=zPG4NjIkCjc and https://www.youtube.com/watch?v=7ArmBVF2dCs

<>p

Applications of statistical methods for the behavioral sciences:

A/B testing, data science, probability and testing: What is A/B Testing? | Data Science in Minutes - YouTube and Crack A/B Testing Problems for Data Science Interviews | Product Sense Interviews - YouTube and A/B testing - Statistical significance for beginners - YouTubeWhich tests to use? How To Know Which Statistical Test To Use For Hypothesis Testing - YouTube

Random Controlled Trials of medications (RCT's): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4966397/

What is an artificial neural network, in the context  of statistical methods: data science, predictions, artificial intelligence and machine learning? https://www.youtube.com/watch?v=aircAruvnKk

https://www.youtube.com/watch?v=POrb5ZogvDs and  https://www.youtube.com/watch?v=9WsL2fdrqGE and https://www.youtube.com/watch?v=9ZfPGEMS

 Data science, artificial intelligence and machine learning: https://www.youtube.com/watch?v=iug8FAl0B1U

Week 8 Review and Second Exam

https://en.wikipedia.org/wiki/Statistics

Statistics, data collection, prediction, and analytics are of fundamental importance in modern society. Students should be able to understand, critique, use, and discuss basic concepts about statistics in behavioral science.

The purpose of this course is primarily practical and applied.  However, the philosophy of statistics, and philosophy of science, will be referenced as well. Major areas will be described and analyzed, particular research method traditions and techniques examined, a historical overview introduced, and relationships to other fields established.  The relevance of research to practical everyday needs, to science, medicine, government, policy, administration, and to industry will be discussed.

Overall, this course will provide students with ideas, concepts, and approaches that will enable them to make contributions to these and other fields, depending on abilities and interest. Current approaches to applying statistical tools, techniques, and methods for problem solving will be emphasized, and, time permitting, researchers will be brought in to demonstrate these.

Grading:

A-90 or above

B 80-89

C 70-79

D 60-69

F below 60