
In this video, you'll discover a clear and intuitive flowchart to help you always know where you're at in the course and what to focus on next. Whether you're starting with no statistics knowledge or need a quick refresh before diving into advanced concepts, this personalised roadmap will guide you based on your current knowledge and learning goals.
Stay on track, focused, efficient and stress free with this tool.
Use it to:
- Assess your current knowledge level
- Identify the most relevant lessons for your needs
- Progress through the course with confidence and clarity
An overview of central tendency in descriptive statistics as well as a way to calculate the three main measures of central tendency; mean, mode and median.
An introduction to Dispersion, including how to calculate the Range and Interquartile Range.
An overview of calculating standard deviation and variance
An introduction to the different types of variables
Identifying variables based off their data type and then conducting the most appropriate summary measures for them
Section 2 Summarised: a concise recap and overview of the topics taught in Section 2. You should feel comfortable with all these topics before moving on to the next section
A glossary of the key terms and concepts you should know by the end of this section
Have a go memorising some terms and getting them into your short-term memory!
Intuitively understand what a z-score is and how to calculate it
Learn the formula and steps for calculating Z-scores
Learn how to use Z-scores to calculate the probability of certain events occurring
Use your knowledge of z-scores and finding the probability to reverse the process and work out a score given a percentile (and mean and standard deviation)
Super condensed summary and overview of Z scores and finding probabilities
A glossary of the key terms and concepts you should know by the end of this section
Flashcard practice for Section 3
An introduction to regression and looking at the line of best fit, including calculating the equation of the linear line through calculating slope and y intercept.
Looking at the slope to suggest whether the independent variable causes the dependent variable (i.e. to see whether there is a relationship) or whether its most likely down to chance. Look in the downloadable materials to delve a bit more into populations and samples and sampling. For the purposes of this course, sampling methods won't be discussed in greater detail. The main takeaway from this lecture is that we often use a sample to make an inferential statement about a population; and that some of the results we observe in the sample may be due to chance.
An overview of statistical inference and sampling, further talking about the importance of sampling and making the distinction between a sample and a population. We'll also talk about how statistical inference allows us to use samples to make statements (or inferences) about the population.
In this video, we want to start attributing likelihood (or probability) to the events that we observe and discuss the concept of sampling variability and how much sampling variability is too much?
CONCISE: brief overview of regression and the line of best fit and how that relates to cause vs chance and probability values
Key concepts for Day 3
Flashcard practice for Day 4
It's the big one! We finally see how hypothesis testing works and how to construct null and alternate hypotheses and the framework required. This is just an intro to it and then we'll document it step by step in a later lecture. I know this lecture is a bit longer, if you're short on time and would like, check out the concise version and then come back here if you need it explained in a bit more detail!
An overview of confidence intervals and what they represent. We talk about how confidence intervals give us a greater understanding of our sample and population and how we can use confidence intervals to do hypothesis testing
A concise summary and overview of hypothesis testing and confidence intervals - if in any doubt after watching this video, go back and look at the detailed videos in this section until you're comfortable with the concepts discussed.
Key concepts you should be familiar with after completing this section
Flashcard practice to get familiar with the terms for hypothesis testing and confidence intervals
Learn which hypothesis test to use and when.
A step by step run down summary of one sample means hypothesis testing
An example of how to solve a one sample hypothesis test question and how to evaluate a claim using this framework.
A step-by-step rundown on the key points of one sample hypothesis testing for proportions
A step-by-step example on how to use the 'critical value method' as well as the 'p value method' to answer one sample proportions hypothesis test claims
Learn how to use the Confidence Interval method for One Sample Proportions to conduct hypothesis testing
An overview of what a one-tail vs two-tail test is and when to use each.
A brief overview of what's been covered so far.
A quick look at what's still to come in the course.
Learn the difference between an independent t-test assuming equal variances vs independent t-test assuming unequal variances and how to tell which one to use.
Concise step-by-step rundown on how to perform an independent samples t-test (either assuming equal variances or not).
A step-by-step overview of the steps and assumptions for a Paired Samples T-test.
Statistics & Probability for Beginners: Lost to Confident
Statistics can often feel like a foreign language - full of jargon, symbols, dense lectures and stress. This course is your stress-free shortcut to finally understanding the core ideas of statistics and probability in just 15 days - no prior knowledge or confidence in maths required!
This course is designed for students who want a complete, intuitive foundation before or during a university statistics course.
Who This Course Is For:
This course is perfect for:
Students in Non-Statistics Degrees
(Psychology, HR, Business, Finance, Law, Public Health):
If you’re in a field that suddenly requires statistics, this course will simplify everything - even if you've never felt confident with numbers.
Complete Beginners who've always struggled with maths:
No prior knowledge? No problem! This course starts from the ground up. You'll be guided step-by-step, without assumptions or jargon.
Career Changers & Professionals:
Learn how to use statistics to analyse data, make smarter decisions, and build practical skills in today’s data-driven world.
Anyone Burned by Traditional Teaching:
If you've sat through dense lectures or confusing textbooks and still felt lost - this course will help it finally click.
Why This Course Is Different & Why Learn From Me?
Built from Experience, Taught with Empathy
I used to be you. Right in your shoes that you're in now - I get how frustrating it feels to be left behind by dense lectures. Just when I'd think I was starting to grasp one concept, we'd quickly jump to something new (seemingly unrelated), and I'd be left behind all over again.
One week before my final exam, I sat down and mapped it all out. I started seeing connections - things that hadn't been emphasised in lectures at all! And I found a way to see the forest among the trees and then the trees themselves. I ended with a high distinction and from then on I've been working with or in stats.
Since then, I’ve tutored thousands of students and professionals across many disciplines, many of whom felt the same fear and confusion. This course is built on everything I've learned from those sessions - the exact techniques and explanations that helped things finally click.
"Jon has explained more to me in 3 sessions than I have learned in 6 weeks of tutes and lectures." - HR student
How This Course Works
Unlike traditional university courses, this one avoids overwhelm and focuses on what you actually need:
Plain English Explanations: Concepts are explained with real world analogies and simple breakdowns
A Simpler Structure: A different flow to the usual first-year statistics structure, built from 1-on-1 tutoring insights
Step-by-Step Progression: Each concept builds logically on the last
A Custom Starting Point: Use the included flowchart to find your starting level and focus on the most relevant material, saving you even more time
Confidence-First Approach: You'll never feel rushed, judged, or talked down to
What You’ll Learn (in Just Two Weeks)
Finally understand why statistics felt so confusing - and why that was never about your ability
Read and interpret data confidently using descriptive statistics - learn how to summarise and display data using means, standard deviation and distributions explained in plain English
Understand probability intuitively and how it connects to real-world decisions
Use regression to spot relationships in data and make predictions, step by step
Run and interpret hypothesis tests - t-tests, ANOVA, chi-square - and actually know what the results are telling you
Understand confidence intervals and p-values without memorising definitions you might forget under pressure
Grasp the Central Limit Theorem and why it matters
Know when your data meets the assumptions required for common statistical tests - including normality
Walk away thinking "that wasn't so bad"
Course Features:
Step-by-Step Walkthroughs: of topics like z-scores, t-tests and ANOVA - each taught in isolation, clearly and simply
Concise Lectures: Use quick summary lessons to revise or revisit key concepts
Interactive Flowchart: Find your level and start in the right place
Real-World Examples: From finance to public health, see how statistics is applied in practical scenarios
Student Testimonials
"Jon tutored me for STATS and was absolutely amazing. I had done the unit previously and put it off until my second last semester to do it again as I dreaded doing it again and had zero confidence in doing well. Jon was patient and super understanding! We set goals for every session, tackling topics I absolutely did not like doing. He helped me write notes that were easy to understand, breaking down the fundamentals of each topic. He made studying for STATS seamless and enjoyable. After a couple of sessions with Jon, I didn’t dread studying for STATS as much anymore and could confidently say that I understood everything right before my exam. Thank you so much for your help, Jon!"
- Psychology student
"Jon tutored me for biostatistics for a semester and WOW what a saviour he has been! He makes understanding difficult concepts easy."
- Public Health student
"I met Jon not knowing a thing about stats, maths and everything in between. Jon tutored me for PUBH and thank goodness I found him. Jon is extremely patient, friendly and you never felt incompetent when giving a question a go. Jon explained things in such a learning friendly manner. Jon provided his own simplified notes (which was a godsend). I cannot recommend Jon enough, and will be forever thankful for his expertise and helping me pass this unit. Thank you Jon!!"
- Public Health student
30-day refund guarantee - so if it's not the right fit, no worries at all.
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Sign up today and take the first step to mastering statistics and probability - your shortcut to success in just 15 days!