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In this exciting and informative video, we take you on a deep dive into the fascinating world of statistics! Whether you're new to the subject or looking to enhance your understanding, we’ve got you covered. We start with a glimpse of what statistics is and then guide you through key concepts like descriptive statistics, inferential statistics, frequency statistics, and kurtosis statistics. To make things even more engaging, we’ve included real-world examples that break down each type of statistics in a way that’s easy to grasp. By the end of the video, you'll not only understand the differences between these types of statistics but also gain practical insights into how they’re applied. This is the perfect guide for anyone eager to confidently navigate the essentials of statistical analysis. Get ready to learn, understand, and apply statistics like never before!
---Frequently Asked Questions
✅What is the difference between descriptive statistics and inferential statistics?
Descriptive statistics uses the data to provide descriptions of the population, either through numerical calculations or graphs or tables. Inferential statistics makes inferences and predictions about a population based on a sample of data taken from the population in question.
✅What is the difference between frequency and descriptive statistics?
Frequency statistics simply count the number of times that each variable occurs, such as the number of males and females within the sample.
✅What is called kurtosis?
Kurtosis is a measure of the tailedness of a distribution. Tailedness is how often outliers occur. Excess kurtosis is the tailedness of a distribution relative to a normal distribution.
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➡️ About Data Science course in collaboration with IBM
This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.
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✅ Skills Covered
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