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Stress-Free Statistics: IBDP/AP and College Students Part 3

Stress-Free Ways to Learn about Regression, Prediction, Probability, Sampling, and Interval Estimation
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Platform: Udemy
Video: 3h 35m
Language: English
Next start: On Demand

Table of contents

Description

of Mini-Course 3
This 14-lesson course includes video and text explanations of regression, prediction, probability, sampling, and interval estimation. It includes practice problems, quizzes and exam questions (with solutions) to help students monitor their understanding at each step along the way. Lessons are short and tight and easy to digest. You can use this curriculum as a stand-alone course or as a supplement to any statistics courses you are currently taking. This course will help you master statistics. It was designed specifically for humanities majors in college or students in secondary school AP and IBDP classes.

Created by Dr. Laura Roberts, Ph.D.

English
Syllabus: Mini-Course 3 is in bold font.
The following syllabus lists each of the 5 mini-courses in context. The current mini-course syllabus, #3, is in bold type.

Mini-Course 1 – The Purpose of Statistics and Descriptive Methods (4.5 hours of video lectures)
Chapter 1 – The Purpose of Statistics
Chapter 2 – Cases, Variables, and Questions
Chapter 3 – Frequency Distributions and Visual Displays of Data
Chapter 4 – Measures of Central Tendency
Chapter 5 – Measures of Variability

Mini-Course 2 – Normal Distribution, Standard Scores, and the Bivariate Normal Distribution (3 hours of video lectures)
Chapter 6 – The Normal Distribution and Standard Scores
Chapter 7 – The Bivariate Normal Distribution

Mini-Course 3 – Regression, Prediction, Probability, Sampling, and Interval Estimation (4.5 hours of video lectures)
Chapter 8 – Regression and Prediction
Chapter 9 – Probability
Chapter 10 – Statistical Inference

Mini-Course 4 – Introduction to Hypothesis Testing (3.3 hours of video lectures)
Chapter 11 – Introduction to Hypothesis Testing

Mini-Course 5 – Estimation issues, the t-distribution, Degrees of Freedom, t-tables, Statistics for Categorical Dependent Variables, and Inferences about Correlation Coefficients (3.25 hours of video lectures)
Chapter 12 – Estimation Issues and the t Distribution
Chapter 13 – Statistics for Categorical Dependent Variables
Chapter 14 – Inferences about Correlations and Fisher’s Z Transformation

The chapters are aligned with those in the following text:

Glass, G. V. & Hopkins, K. D. (1996). Statistical Methods in Education and Psychology. Needham Heights, MA: Allyn & Bacon

You may enroll for the entire course or pick and choose among the 5 Mini-Courses, depending on your needs. The entire course includes
· 17+ hours of on-demand video
· 68+ powerpoint presentations including notes/transcripts
· Over 100 quiz and exam questions plus answer keys and explanations!
· 100+ downloadable resources
· Access on mobile and TV
Designed for all statistics students, including non-math majors, non-STEM majors, arts, humanities, liberal arts, EDUCATIONAL LEADERSHIP STUDENTS, education majors, and nursing students. In short it is for all students seeking an effective and accessible online Statistics Course.
For courses that are offered fully online, these materials can be used as a stand-alone statistics curriculum.
Alternatively, the materials can be used to supplement any text or coursework students are currently taking.

Often, educators want to describe a set of characteristics of a group of people. For example, teachers may want to describe how much time their students spend on homework, or how resilient and empathic their students are, or any number of other characteristics. In this course, educators will learn how to describe characteristics of people in the following ways:
· suppose an educator could boil down set of numbers to a single number (e.g. how many minutes a typical student spends on homework each night); what would be the best number to represent the typical values? These statistics could be used: mean, median, or mode.
· Of course, not all students study the same amount each night. So, one may want to know how much students’ scores tend to vary around the typical value. These statistics could be used: range, variance, and standard deviation.
· Suppose an educator wants to show time spent on homework to a parent group. Instead of presenting a long list of numbers and watching the parents’ eyes glaze over, the educator may want to create visual or graphic “pictures” of the numbers (data). These statistical methods could be used: bar graphs, histograms, and scatterplots.
· With these foundational ideas (typical value, variation around the typical value, visual “pictures” of the data, educators can then understand and effectively use the following higher level statistics:
· using a sample mean and standard deviation to estimate a population mean and standard deviation. In other words, using a typical value (such as a mean) and typical variation (such as a standard deviation) of a small group of students to estimate a typical value and typical variation of a large group of students. Think of how much time (and money) an educator can save by gathering data on a small group and using that information to make estimates for a larger group (with a precise degree of confidence). For example, an educator could assess the time spent on homework from a small number of students and derive an estimate of time spent on homework for the whole school.
· Suppose an educator wanted to know if time spent on homework was correlated with the extent to which parents value learning. An educator can use statistics to find out how much these two characteristics (or variables) are correlated. In other word, is time spent on homework greater when parents place a higher value on learning?
· make predictions about the future using past information. For example, suppose a growing number of teachers were calling in sick due to a virus spreading through the school. For example, suppose the number of absentees double each day. The principal needs to know how many substitute teachers they will need next week and the week after. A principal could estimate the number of absentees next week and the week after (assuming no steps were taken to stop the virus.)
Students will also understand the following statistical methods (the usefulness of these statistics will become clearer as the course progresses):
· working with special characteristics of normal distributions and z-scores.
· understanding probability with fun games of chance such as cards and dice.
· understanding important probability-related concepts such as union, intersection, independent events, dependent events, and Bayes’ theorem.
· make inferences about nonparametric variables (i.e. grouping variables, e.g. “special needs students” versus “not special needs students.”)
Requirements
· The most important requirements are a willingness to keep an open mind, a ready spirit, and dedication to the topic.
· The second most important requirement is a willingness to let go of math anxiety.
The following math skills are a plus, but, be assured, explanations will begin at a basic level and build gradually to higher and higher levels of complexity:
· Knowledge of arithmetic (addition, subtraction, multiplication, division) of whole numbers.
· Knowledge of basic algebraic operations and simple equation solving.
EACH LESSON INCLUDES:
Video Tutorials: I present each lesson in short, easily-digestible chunks. I begin with an overview of the lesson; then I explain each concept in careful detail including concrete examples; and I conclude with a summary and segue to the next lesson. Students will also find each lesson has a fun, entertaining aspect because I have illustrated each one with abstract art from around the world. The great thing about learning with narrated video tutorials is students can stop the action at any point and go over the concept again if it doesn’t “land” the first time through. My modus operandi when I created these videos was to distill the topic down to the essential concepts and to present a streamlined, elegant version of each statistical concept. Many stats textbooks present unnecessary overkill and students become overwhelmed and discouraged. I think students will find my method a refreshing alternative to the traditional method.
Notes: Students will also get an inside peek into all the powerpoint slides with notes and transcripts for each lesson. These lessons are to statistics what Sparknotes are for books. Students will find the essential concepts without the showy overkill that appears in lots of textbooks.
Quizzes: At each step along the way, students can test their knowledge with quizzes and practice problems. I have also provided them with the answer keys, worked problems, and careful explanations of each answer. I have confidence that students will have a great experience with my teaching method.
HERE’S WHAT SOME STUDENTS HAVE TOLD ME ABOUT “COLLEGE STATISTICS FOR NON-MATH MAJORS” AND MY TEACHING APPROACH:
“I think Dr. Roberts is the BEST at teaching practical statistics to…students. The materials she has developed are useful and help make the complex simple and understandable.”
Dr. George White,
Professor of Education at Lehigh University, Bethlehem, PA,
Coordinator of the Educational Leadership Program
Dr. Laura Roberts has been an exceptional resource for my study. She is a stellar statistician and dissertation consultant. She raised the quality of my paper by helping me with the design of the study and then, working with me through the subsequent data analysis.

David Harris, Oxford Learning Centre
Cambridge, Ontario
Dr. Roberts is one of the best professors I have had in my higher education in terms of both her teaching strategies and her content expertise in statistics and research methods. Statistics and mathematics have always been challenging subjects for me. Although I passed my university statistics courses with top grades, I did not truly understand most statistical methods. In addition, the complexity of statistical methods I used in my dissertation study far exceeded any methods I learned about in my doctoral courses. Dr. Roberts is patient, she uses visual models, and she gives detailed and precise explanations that make even the most complex statistics easier to understand. To be clear, however, she also did not spoon-feed me with answers nor do the hard work for me. Rather, she would give examples, then she would ask deep, thought provoking questions, requiring me to explain my thinking and demonstrate my understanding. Dr. Roberts is skilled at designing assessments and giving valuable feedback. Every time I sent another draft of my dissertation, Dr. Roberts offered a thoughtful balance of authentic compliments and detailed critique. Without coming off as demanding in a negative way, she was able to push, prod and convince me to keep at my writing and improve it beyond any level I would have previously imagined I was capable. Dr. Roberts has a passion for research that is contagious. Before I started the doctoral program, I really did not intend to continue in scholarly research. I was motivated to earn the degree for professional reasons, but I did not necessarily value being a scholar researcher. As a direct result of Dr. Roberts’s encouragement and enthusiasm, I have presented my dissertation findings at professional conferences, and I am working towards publishing articles in peer-reviewed journals. Dr. Laura Roberts has my highest recommendation for anyone looking for an outstanding mentor in research/statistical methods and dissertation writing. She also has my unreserved recommendation for any teaching or research position in higher education. She is an exceptional professor and researcher. Any higher research and education institution would be lucky to have her on their faculty.
Sean Areias, Ed.D.
Interim Superintendent
American International School of Lagos
Laura’s greatest skill is her work with statistics – not only bringing the highest level of quantitative analysis to the data, but “translating” it into layman’s terms for her collaborators and a wider audience to appreciate.
Steve Mancuso
Superintendent of Colegio
Internacional Puerta La Cruz
Dr. Laura Roberts is a multi talented researcher, doctoral coach, professor of qualitative and quantitative statistics courses and many many other talents. She has been a doctoral mentor to a variety of international school heads, superintendents of schools and hundreds of educators. She has presented at and attended AAIE and the CP Task Force meeting we held at the US Department of State. She is a scholar of high repute and…a wonderful mentor and guide.
Christine Brown, Ed.D
US State Department Liaison to the European Council of International Schools
Is this course a good match for you?
Are you a non-math major who is required to take statistics? Do you break into a cold sweat at the thought of facing another required stat assignment? Have you searched the web looking for help and found nothing that really works for you?
Relax. You’re in the right place.
My name is Dr. Laura Roberts and I was a student just like you. I was a nervous wreck class after stat class. Dropping wasn’t an option – I needed those classes to graduate. And what I discovered after I earned my doctorate and began teaching my own classes … was this.
Learning statistics doesn’t have to be scary.
Over time, I developed teaching methods that my students found effective. They learned without the frustration and the stress – and they passed their classes with flying colors!
I’m the stat guru behind Right Angle Educators. I’ve put together a series of video tutorials that will help you grasp statistical concepts quickly and easily.
What do my video tutorials have that other online statistics videos do not have?
· Unit objectives
· Lesson objectives
· Type-written slides (believe it or not, many online videos offered by other companies are in hand-written script that is very hard to read.)
· Clearly sequenced and integrated lesson presentations
User friendly lessons that are based on my 30+ years of experience as a statistics professor. I found many students have high math anxiety. High anxiety interferes with learning. My approach is intentionally designed to lower students’ anxiety and increase their learning.
There are many reasons for this, but one of the biggest? Students don’t “get” the statistical skills necessary for original research. This course will give them everything they need to design and carry out their study.
Okay, so let’s get started. My materials will calm your fears and get you feeling like top-notch number cruncher in no time at all.

You will learn

✓ Students will learn to compute Regression analysis.
✓ Students will learn how to use regression analysis to predict outcomes.
✓ Students will learn how to use probability to interpret regression analyses.
✓ Students will learn how to estimate intervals for given parameters.
✓ Students will learn how to find a small sample of people who will provide a good idea of behavior for a much larger population of people
✓ Students will learn how to use a mean score for a small group of people to estimate a mean score for a large group of people
✓ Students will learn how statistics and sampling methods can make research less expensive and less time-consuming
✓ Students will learn how to interpret the slope of a line

Requirements

• Algebra
• Geometry
• The course does not require knowledge of trigonometry or calculus.
• The course requires students to approach statistics learning in a fresh, new way.
• This course requires students to be willing to leave their math and statistics anxiety behind.
• This course requires students to approach statistics in a playful way
• This course requires students to leave behind notions of statistics as dry and boring

This course is for

• Students in AP and IBDP Programs, Including Math-Anxious Students
• Students in undergraduate social science programs
• Students in doctoral level social science programs
• Students in doctoral level programs in educational leadership
• Students who need extra support using statistics to write their dissertation
• Doctoral students conducting original research
• Doctoral students conducting quantitative research
• Undergraduate students conducting quantitative research
• AP and IBDP students conducting quantitative research
Professor of Research Methods and Statistics, Director RAE
I have been teaching research methods and statistics for 30 years and have mentored more than 300 students, guiding them successfully from ABD to Ph.D. I am also Director of Research and Statistics Education at Right Angle Educators. I have created this course on research statistics. Students can supplement any course they are taking by adding this course to boost their knowledge. University department heads are welcome to peruse the course to see if there is a fit for your program. The course can be offered as a stand-alone curriculum to prepare your students in all statistical areas needed for doctoral level research.
Browse all courses by on Coursemarks.
Platform: Udemy
Video: 3h 35m
Language: English
Next start: On Demand

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