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Ali Helmi
By the end of this project, you will be able to interpret the results of central tendency measures (Mean, Median and Mode)and calculate them step by step using built-in functions in Google Sheets. Moreover, You will be able to identify the most popular...
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By the end of this project, you will be able to interpret the results of central tendency measures (Mean, Median and Mode)and calculate them step by step using built-in functions in Google Sheets. Moreover, You will be able to identify the most popular variability measures such as the range, interquartile range (IQR), variance, and standard deviation. After you complete this project, you will have enough knowledge to start working on many datasets by exploring it and identifying the most important measures in Descriptive Statistics. You will also have the ability to recognize outliers values in your data set and interpret the measure of statistical dispersion. This project will give you a head start into data analysis using google sheets. We will be working on a cleaned dataset with no missing/null values. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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Builds a strong foundation for beginners by teaching the basics of descriptive statistics and data exploration using Google Sheets
Useful for learners who want to gain practical experience in data exploration and analysis using Google Sheets
Suitable for individuals interested in data analysis and visualization, particularly those who are comfortable with using Google Sheets

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Reviews summary

Google sheets descriptive statistics review

The course on Descriptive Statistics was rated poorly by students. Students noted errors in the lectures and opined that the content was too simple for most students.
The content was too basic.
"Simple contents"
The lectures contained errors.
"There are errors... The mode was 74 not 47."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Descriptive Statistics Using Google Sheets with these activities:
Review Probability and Statistical Distributions
Strengthens your understanding of probability and statistical distributions, which are foundational concepts for data analysis.
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  • Go over the basics of probability theory.
  • Review common statistical distributions, such as normal, binomial, and Poisson.
  • Solve practice problems to reinforce your understanding.
Review Basics of Descriptive Statistics
Helps refresh your foundational understanding of Descriptive Statistics, making it easier to grasp concepts taught in this course.
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  • Revisit the concepts of mean, median, and mode.
  • Review the definitions and formulas of range, interquartile range, variance, and standard deviation.
  • Work through practice problems to reinforce your understanding.
Organize Course Materials
Helps you stay organized by compiling and reviewing course materials regularly, improving retention and accessibility.
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  • Gather and organize notes, assignments, and quizzes.
  • Review and summarize key concepts.
  • Identify areas for further study.
Eight other activities
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Study Group Discussions
Facilitates peer learning and encourages discussions on course concepts, fostering a deeper understanding.
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  • Form a study group with classmates.
  • Meet regularly to discuss course material.
  • Share insights, ask questions, and clarify concepts.
Learn About Statistical Measures Using Tutorials
Tutorials can provide clear and structured explanations of statistical measures, enhancing your understanding.
Show steps
  • Search for online tutorials on central tendency measures and variability measures.
  • Watch or read the tutorials carefully, taking notes on key concepts.
  • Complete any practice exercises or quizzes provided in the tutorials.
Explore Additional Google Sheets Functions
Expands your knowledge of Google Sheets functions beyond those covered in the course, enhancing your data analysis capabilities.
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  • Research and identify additional Google Sheets functions.
  • Review tutorials or documentation to understand how to use them.
  • Experiment with the functions in real-world scenarios.
Solve Google Sheets Problems
Solving problems will reinforce your knowledge of central tendency measures and variability measures.
Show steps
  • Find and collect Google Sheets problems online.
  • Solve the problems step-by-step.
  • Check your answers and identify areas where you need improvement.
Calculate Descriptive Statistics Using Google Sheets
Provides hands-on practice in calculating descriptive statistics using Google Sheets, a tool used in the course.
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  • Create a dataset in Google Sheets.
  • Use the built-in functions for mean, median, mode, range, interquartile range, variance, and standard deviation.
  • Interpret the results and identify patterns in the data.
Create a Google Sheets Template
Creating a template will help you organize and analyze data effectively, consolidating your knowledge of descriptive statistics.
Show steps
  • Design a Google Sheets template to calculate central tendency measures and variability measures.
  • Use conditional formatting to highlight outliers and trends.
  • Share your template with others to receive feedback and improve your work.
Data Analytics Challenge
Provides a real-world application of descriptive statistics to solve a specific problem, enhancing your analytical and problem-solving skills.
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  • Identify a real-world problem that can be addressed using data analytics.
  • Collect and analyze relevant data using descriptive statistics.
  • Develop a solution to the problem based on your analysis.
  • Present your solution to stakeholders.
Data Analysis Project
Encourages you to apply your knowledge of descriptive statistics to analyze a real-world dataset and present your findings.
Browse courses on Data Analysis
Show steps
  • Choose a dataset that interests you.
  • Calculate descriptive statistics and identify key insights.
  • Create visualizations and draw conclusions from your analysis.
  • Write a report summarizing your findings.

Career center

Learners who complete Introduction to Descriptive Statistics Using Google Sheets will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use data to solve problems and make informed decisions. They work with data from a variety of sources, including databases, spreadsheets, and surveys. The course on Introduction to Descriptive Statistics Using Google Sheets can provide Data Scientists with the skills they need to collect, analyze, and interpret data. This course will help Data Scientists to understand the different types of descriptive statistics, and how to use them to summarize and describe data.
Business Analyst
A Business Analyst identifies opportunities for improvement within an organization. They use data analysis to understand the current state of the business, and then develop and implement solutions to improve efficiency and effectiveness. The course on Introduction to Descriptive Statistics Using Google Sheets can provide Business Analysts with the skills they need to collect, analyze, and interpret data. This course will help Business Analysts to identify trends and patterns in data, and to make informed decisions about how to improve the business.
Statistician
Statisticians collect, analyze, interpret, and present data. They work in a variety of fields, including healthcare, education, and government. The course on Introduction to Descriptive Statistics Using Google Sheets can provide Statisticians with the skills they need to clean, analyze, and interpret data. This course will help Statisticians to understand the different types of descriptive statistics, and how to use them to summarize and describe data.
Data Analyst
Data Analysts use data to solve problems and make informed decisions. They work with data from a variety of sources, including databases, spreadsheets, and surveys. The course on Introduction to Descriptive Statistics Using Google Sheets can provide Data Analysts with the skills they need to clean, analyze, and interpret data. This course will help Data Analysts to understand the different types of descriptive statistics, and how to use them to summarize and describe data.
Market Research Analyst
Market Research Analysts collect and analyze data about markets, customers, and competitors. They use this information to help businesses make informed decisions about product development, marketing campaigns, and pricing. The course on Introduction to Descriptive Statistics Using Google Sheets can provide Market Research Analysts with the skills they need to collect, analyze, and interpret data. This course will help Market Research Analysts to understand the different types of descriptive statistics, and how to use them to summarize and describe data.
Economist
Economists study the production, distribution, and consumption of goods and services. They use data to analyze economic trends and make recommendations about economic policy. The course on Introduction to Descriptive Statistics Using Google Sheets can provide Economists with the skills they need to collect, analyze, and interpret data. This course will help Economists to understand the different types of descriptive statistics, and how to use them to summarize and describe data.
Financial Analyst
Financial Analysts use data to make recommendations about investments and financial planning. They work with a variety of financial data, including stock prices, earnings reports, and economic indicators. The course on Introduction to Descriptive Statistics Using Google Sheets can provide Financial Analysts with the skills they need to collect, analyze, and interpret data. This course will help Financial Analysts to understand the different types of descriptive statistics, and how to use them to summarize and describe data.
Risk Analyst
Risk Analysts use data to assess and manage risk. They work in a variety of industries, including insurance, finance, and healthcare. The course on Introduction to Descriptive Statistics Using Google Sheets can provide Risk Analysts with the skills they need to collect, analyze, and interpret data. This course will help Risk Analysts to understand the different types of descriptive statistics, and how to use them to summarize and describe data.
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. They use data to train models that can learn from data and make predictions. The course on Introduction to Descriptive Statistics Using Google Sheets can provide Machine Learning Engineers with the skills they need to collect, analyze, and interpret data. This course will help Machine Learning Engineers to understand the different types of descriptive statistics, and how to use them to summarize and describe data.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. They work in the financial industry, helping to make investment decisions. The course on Introduction to Descriptive Statistics Using Google Sheets can provide Quantitative Analysts with the skills they need to collect, analyze, and interpret data. This course will help Quantitative Analysts to understand the different types of descriptive statistics, and how to use them to summarize and describe data.
Operations Research Analyst
Operations Research Analysts use mathematical models to solve problems in a variety of industries, including manufacturing, healthcare, and finance. They use data to analyze problems and develop solutions that can improve efficiency and effectiveness. The course on Introduction to Descriptive Statistics Using Google Sheets can provide Operations Research Analysts with the skills they need to collect, analyze, and interpret data. This course will help Operations Research Analysts to understand the different types of descriptive statistics, and how to use them to summarize and describe data.
Actuary
Actuaries use mathematics and statistics to assess and manage risk. They work in a variety of industries, including insurance, finance, and healthcare. The course on Introduction to Descriptive Statistics Using Google Sheets can provide Actuaries with the skills they need to collect, analyze, and interpret data. This course will help Actuaries to understand the different types of descriptive statistics, and how to use them to summarize and describe data.

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Introduction to Descriptive Statistics Using Google Sheets.
Classic textbook on statistics for research. It covers a wide range of topics, including descriptive statistics, inferential statistics, and regression analysis.
Comprehensive textbook on statistical methods for the social sciences. It covers a wide range of topics, including descriptive statistics, inferential statistics, and regression analysis.
Valuable resource for those who are new to statistics or who need a refresher. It provides a clear and concise overview of the basic principles of statistics, including descriptive statistics, inferential statistics, and regression analysis.
Practical guide to data science for business professionals. It covers a wide range of topics, including data cleaning, data visualization, and statistical analysis.
Practical guide to data analysis for those with no prior knowledge of the subject. It covers a wide range of topics, including data cleaning, data visualization, and statistical analysis.
Practical guide to deep learning with Python. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks.
Practical guide to natural language processing with Python. It covers a wide range of topics, including text preprocessing, text classification, and text generation.
Practical guide to Bayesian statistics with R and Stan. It covers a wide range of topics, including Bayesian inference, Bayesian modeling, and Bayesian computation.

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