Statistics is an important field of math that is used to analyze, interpret, and predict outcomes from data. Descriptive statistics will teach you the basic concepts used to describe data. This is a great beginner course for those interested in Data Science, Economics, Psychology, Machine Learning, Sports analytics and just about any other field.
Overview
Syllabus
- Intro to Research Methods
- Introduction to several statistical study methods.,Learn the positives and negatives of each.
- Visualizing Data
- Take your data and display it to the world.,Create and interpret histograms, bar charts, and frequency plots.
- Central Tendency
- Compute and interpret the 3 measures of center for distributions: the mean, median, and mode.
- Variability
- Quantify the spread of data using the range and standard deviation.,Identify outliers in data sets using the concept of the interquartile range.
- Standardizing
- Convert distributions into the standard normal distribution using the Z-score.,Compute proportions using standardized distributions.
- Normal Distribution
- Use normalized distributions to compute probabilities,Use the Z-table to look up the proportions of observations above, below, or in between values
- Sampling Distributions
- Apply the concepts of probability and normalization to sample data sets.
Taught by
Katie Kormanik, Ronald Rogers and Sean Laraway
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Reviews
4.0 rating, based on 12 Class Central reviews
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Pushkar DkA lot of people here have found this course boring. I think it is slow paced so that anyone can easily understand the material. In my opinion, there are enough quizzes and exercises to keep our minds occupied and it's not boring!
The way things have been explained in this course, both according to visualization of variables and the use of real-world examples, has been excellent!
This course lays the foundation for another course on Udacity called `Intro to Inferential Statistics` and that course has been rated very high on Class Central which is why I think *this* course is important. -
The course is quite boring. Lets you perform boring counting and numerical tasks with little focus on actual statistics. Though, by the end of the class things improved. There is at least one serious error in exercises, where you have to answer question on factual data provided on previous slide and have to go there and back between 2 slides. Also some concepts are mentioned and used early in the class but introduced only later on. I miss more mathematical derivation of formulas e.g. SE.
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Pros :
# Starts from the very beginning of statistics
#Introduces most fundamental concepts of descriptive statistics
#This course is a part of Nanodegree (Just like specialization in coursera) and pushes you on the track of next course which is inferential statistics
Cons:
#Boring course with unnecessary videos and countings. May be instructor tried to make the course too easy but it made the course unnecessarily lengthy. -
It was good revision of everything. All concepts and formulas I had forgotten over a period of time. Looking forward for more such courses. It took me less than a month to complete the course. The instructor is very clear with her explanations.
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Laurynas Zubko -
