Free online courseStatistics Course for Beginners
Duration of the online course: 9 hours and 48 minutes
New course
Learn the basics of statistics with this comprehensive beginner’s course. Explore key concepts like data visualization, hypothesis testing, ANOVA, regression, and more. Enroll now!
Course Description
Welcome to the "Statistics Course for Beginners." Perfectly designed for those new to statistics, this comprehensive course offers a duration of 9 hours and 48 minutes to thoroughly cover fundamental statistical concepts.
In the introduction, you'll delve into an overview of the course, encapsulating the essentials of what you will learn and exploring why this course is hailed as one of the best introductory statistics courses available.
The journey begins with a series of video tutorials that provide a broad yet detailed look at the statistics curriculum. Terminologies and definitions will be explained, ensuring you are familiar with the essential language of statistics.
One of the most critical aspects of any study is the design. This section covers various study designs, including cross-sectional, case-control, and cohort studies, giving you insight into how to structure your statistical inquiries.
Understanding variables and their types is crucial in any statistical analysis. You'll learn to distinguish between different types of variables and the applications of bar charts, pie charts, and frequency tables in representing data.
For those interested in visual data representation, the course explores histograms and density plots for numeric data, as well as boxplots and plots for two variables, providing the skills needed to graphically summarize data effectively.
Distributions are a cornerstone of statistical analysis. You'll learn to describe distributions in terms of center and spread and gain insights into key metrics like mean, median, mode, percentiles, quantiles, and quartiles.
Key components like standard deviation, understanding the difference between sample and population, and the normal distribution are covered extensively. You'll also explore the concept of Z-scores and the relevance of the Central Limit Theorem.
Confidence intervals and hypothesis testing form the backbone of inferential statistics. This course offers thorough explanations of these concepts, alongside practical examples to heighten your understanding of the material.
Deep dive into specialized topics such as the t-distribution, margin of error, bootstrapping, and resampling techniques. You’ll learn to compare confidence intervals and hypothesis tests to draw more precise conclusions from your data.
When it comes to hypothesis testing, you'll understand one-sided versus two-sided alternatives and gain insights into errors and power in hypothesis testing and the intricacies of power calculations.
Move beyond single-variable analysis with bivariate analysis, exploring its meaning and practical applications through categorical data and various tests such as the paired t-test and Wilcoxon signed rank test.
For those comparing groups, the two-sample t-test is discussed, including considerations of equal versus unequal variance assumptions and bootstrap methods for hypothesis testing and creating confidence intervals.
ANOVA or Analysis of Variance offers a robust method for assessing differences among group means. This section covers all necessary details, from introduction to the computation of F-statistic and p-values, and includes the Bonferroni correction for multiple comparisons.
Broaden your statistical toolkit with tests such as the Chi-square test for independence and measures like odds ratios, relative risks, and risk differences, specifically in the context of case-control studies.
Conclude your journey with a focus on simple linear regression, underst.
Conteúdo do Curso
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Video class: Statistics Course Overview | Best Statistics Course | MarinStatsLectures
0h14m
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Exercise: In an introductory statistics course, what is an example of a numeric summary statistic used to summarize a sample?
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Video class: Statistics Video Tutorials at a Glance | Best Statistics Tutorials | MarinStatsLectures
0h02m
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Video class: Statistics Terminology and Definitions| Statistics Tutorial | MarinStatsLectures
0h09m
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Exercise: In the context of statistical analysis, what does inferential statistics aim to accomplish?
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Video class: Study Designs (Cross-sectional, Case-control, Cohort) | Statistics Tutorial | MarinStatsLectures
0h11m
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Video class: Variables and Types of Variables | Statistics Tutorial | MarinStatsLectures
0h13m
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Exercise: What is the correct term for variables that can take on integer values, potentially ranging up to infinity, but cannot be fractions?
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Video class: Bar Chart, Pie Chart, Frequency Tables | Statistics Tutorial | MarinStatsLectures
0h07m
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Video class: Histograms and Density Plots for Numeric Variables | Statistics Tutorial | MarinStatsLectures
0h07m
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Exercise: What is the main advantage of using kernel density plots over histograms?
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Video class: Boxplots in Statistics | Statistics Tutorial | MarinStatsLectures
0h08m
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Video class: Plots for Two Variables | Statistics Tutorial | MarinStatsLectures
0h09m
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Exercise: Which of the following is an appropriate plot to analyze the relationship between a categorical and a numeric variable?
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Video class: Describing Distributions: Center, Spread
0h07m
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Video class: Mean, Median and Mode in Statistics | Statistics Tutorial | MarinStatsLectures
0h10m
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Exercise: Which measure of central tendency is known for being robust, meaning it is not sensitive to outliers or extreme values in a dataset?
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Video class: Percentiles, Quantiles and Quartiles in Statistics | Statistics Tutorial | MarinStatsLectures
0h07m
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Video class: Standard Deviation
0h11m
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Exercise: What is the reason for using the (n-1) term in the denominator when calculating the sample standard deviation rather than just 'n'?
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Video class: Sample and Population in Statistics | Statistics Tutorial | MarinStatsLectures
0h09m
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Video class: Normal Distribution, Z-Scores
0h09m
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Exercise: According to the 68, 95, 99.7 rule for a normal distribution, if the mean height of a population is 175 cm with a standard deviation of 10 cm, what percentage of the population will have heights between 155 cm and 195 cm?
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Video class: Samples from a Normal Distribution | Statistics Tutorial #4 | MarinStatsLectures
0h05m
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Video class: Central Limit Theorem
0h07m
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Exercise: What is the central limit theorem?
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Video class: Standard Error of the Mean: Concept and Formula | Statistics Tutorial #6 | MarinStatsLectures
0h05m
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Video class: Confidence Interval Concept Explained | Statistics Tutorial #7 | MarinStatsLectures
0h08m
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Exercise: What is the standard error of the mean used to estimate when constructing a confidence interval for a single mean?
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Video class: Hypothesis Testing Explained | Statistics Tutorial | MarinStatsLectures
0h09m
Statistics basics
Free Courses on Statistics Basics
Are you looking to build a strong foundation in statistics? Our curated list of free courses on Statistics Basics is designed to help you grasp the essential concepts and techniques of statistical analysis. Whether you're a beginner or looking to refresh your knowledge, these courses cover everything you need to know about the fundamentals of statistics.
Statistics is a crucial field that empowers you to make informed decisions based on data. From understanding descriptive statistics to mastering inferential statistics, our selection of free courses will guide you through each step of the learning process. These courses are perfect for students, professionals, or anyone interested in acquiring statistical skills.
Here’s what you can expect from our free Statistics Basics courses:
- Descriptive Statistics: Learn how to summarize and describe the main features of a dataset. Understand measures of central tendency, variability, and data visualization techniques.
- Probability Theory: Dive into the fundamentals of probability, including probability distributions, random variables, and the laws of probability.
- Inferential Statistics: Gain insights into making predictions or inferences about a population based on a sample. Explore hypothesis testing, confidence intervals, and p-values.
- Regression Analysis: Understand the relationship between variables using linear regression models. Learn how to interpret regression coefficients and make predictions.
- Statistical Software: Get hands-on experience with popular statistical software like R, Python, and Excel. Learn how to perform statistical analysis using these tools.
Each course is structured to provide a comprehensive learning experience, complete with video lectures, interactive exercises, and quizzes to test your knowledge. The best part? These courses are entirely free, making it easy for you to start learning without any financial commitment.
Why choose our free courses on Statistics Basics?
- Expert Instructors: Learn from experienced educators and industry professionals who are passionate about teaching statistics.
- Flexible Learning: Study at your own pace with courses that are available online, anytime, and anywhere.
- Comprehensive Curriculum: Cover all the essential topics in statistics, ensuring you build a solid foundation.
- Interactive Content: Engage with interactive content, including video tutorials, practical exercises, and real-world examples.
- Community Support: Join a community of learners where you can ask questions, share insights, and collaborate with peers.
Don’t miss out on this opportunity to enhance your statistical knowledge. Enroll in our free courses on Statistics Basics today and take the first step towards mastering the art of data analysis.
Ready to get started? Browse our list of free courses below and choose the one that best fits your learning goals:
- Introduction to Descriptive Statistics
- Fundamentals of Probability Theory
- Basics of Inferential Statistics
- Introduction to Regression Analysis
- Statistical Analysis with R
- Excel for Statistical Analysis
- Python for Data Science and Statistics
Start your journey in statistics today and unlock the power of data with our free courses on Statistics Basics!
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