Introduction to fundamentals of statistics

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Introduction to fundamentals of statistics

A population often consists of a large group of specifically defined elements. For example, the population of a specific country means all the people living within the boundaries of that country.

Usually, it is not possible or practical to measure data for every element of the population under study. We randomly select a small group of elements from the population and call it a sample. Inferences about the population are then made on the basis of several samples. Data is quantitative if the observations or measurements made on a given variable of a sample or population have numerical values. Example: height, weight, number of children, blood pressure, current, voltage.

Data is qualitative if words, groups and categories represents the observations or measurements. Example: colors, yes-no answers, blood group.

Fundamentals of Statistics

Quantitative data is discrete if the corresponding data values take discrete values and it is continuous if the data values take continuous values.

Example of discrete data: number of children, number of cars. Example of continuous data: speed, distance, time, pressure. Free Mathematics Tutorials. About the author Download E-mail.

Introduction to Statistics

Introduction to Statistics What is Statistics? Statistics is a mathematical science including methods of collecting, organizing and analyzing data in such a way that meaningful conclusions can be drawn from them. In general, its investigations and analyses fall into two broad categories called descriptive and inferential statistics. Descriptive statistics deals with the processing of data without attempting to draw any inferences from it.

The data are presented in the form of tables and graphs. The characteristics of the data are described in simple terms. Events that are dealt with include everyday happenings such as accidents, prices of goods, business, incomes, epidemics, sports data, population data. Inferential statistics is a scientific discipline that uses mathematical tools to make forecasts and projections by analyzing the given data. This is of use to people employed in such fields as engineering, economics, biology, the social sciences, business, agriculture and communications.

Introduction to Population and Sample A population often consists of a large group of specifically defined elements. Example 1 A company is thinking about buying 50, electric batteries from a manufacturer.

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It is not possible to test each battery in the population of 50, batteries since it takes time and costs money. Instead, it will select few samples of batteries each and test them for defects.

The results of these tests will then be used to estimate the percentage of defective batteries in the population.Download the video from iTunes U or the Internet Archive.

Fundamentals of Statistics - PowerPoint PPT Presentation

The rest of the lectures were recorded in Fallbut video of Lecture 1 was not available. The following content is provided under a Creative Commons license. And it's called Fundamentals of Statistics. And until last spring, it was still called Statistics for Applications. It turned out that really, based on the content, "Fundamentals of Statistics" was a more appropriate title. I'll tell you a little bit about what we're going to be covering in class, what this class is about, what it's not about.

I realize there's several offerings in statistics on campus. So I want to make sure that you've chosen the right one. And I also understand that for some of you, it's a matter of scheduling.

I need to actually throw out a disclaimer. I tend to speak too fast. I'm aware that. Someone in the back, just do like that when you have no idea what I'm saying. Hopefully, I will repeat myself many times. So if you average over time, you'll see that statistics will tell you that you will get the right message that I was actually trying to stick to send.

All right, so what are the goals of this class? The first one is basically to give you an introduction. No one here is expected to have seen statistics before, but as you will see, you are expected to have seen probability. And usually, you do see some statistics in a probability course.

So I'm sure some of you have some ideas, but I won't expect anything. And we'll be using mathematics. Math class, so there's going to be a bunch of equations-- not so much real data and statistical thinking.

We're going to try to provide theoretical guarantees. We have two estimators that are available for me-- how theory guides me to choose between the best of them, how certain can I be of my guarantees or prediction?

It's one thing to just bid out a number. It's another thing to put some error bars around. And we'll see how to build error bars, for example. You will have your own applications. I'm happy to answer questions about specific applications.

But rather than trying to tailor applications to an entire institute, I think we're going to work with pretty standard applications, mostly not very serious ones. And hopefully, you'll be able to take the main principles back with you and apply them to your particular problem.Fundamentals of Statistics covers topics on the introduction, fundamentals, and science of statistics.

The book discusses the collection, organization and representation of numerical data; elementary probability; the binomial Poisson distributions; and the measures of central tendency. The use of control charts for sample means; the ranges and fraction defective; the chi-squared distribution; the F distribution; and the bivariate distributions are also considered.

The book deals with the idea of mathematical expectation and its relationship with mean, variance, and covariance, as well as weighted averages, death rates, and time series. Students studying for advanced level education or higher national certificates in Mechanical or Electrical Engineering, Mathematics, Chemistry, Biology, or Pharmacy, as well as university students taking such courses will find the book invaluable.

We are always looking for ways to improve customer experience on Elsevier. We would like to ask you for a moment of your time to fill in a short questionnaire, at the end of your visit. If you decide to participate, a new browser tab will open so you can complete the survey after you have completed your visit to this website. Thanks in advance for your time. Skip to content. Search for books, journals or webpages All Pages Books Journals.

However, due to transit disruptions in some geographies, deliveries may be delayed. View on ScienceDirect. Authors: H. Mulholland C. Imprint: Butterworth-Heinemann. Published Date: 1st January Page Count: Flexible - Read on multiple operating systems and devices.

introduction to fundamentals of statistics

Easily read eBooks on smart phones, computers, or any eBook readers, including Kindle. Institutional Subscription. Free Shipping Free global shipping No minimum order. Preface 1. Introduction 2. The Collection of Data 2. The Classification of Data 2. Graphical Representation of Data 2. Random Sampling 2.

Random Numbers 2. How to Use Random Sampling Numbers 3. Elementary Probability 3. Introduction 3. Mutually Exclusive Events 3. Independent Events 3. Introduction to Permutations and Combinations 3.From Statistics For Dummies, 2nd Edition. By Deborah J. Being able to make the connections between those statistical techniques and formulas is perhaps even more important. It builds confidence when attacking statistical problems and solidifies your strategies for completing statistical projects.

After data has been collected, the first step in analyzing it is to crunch out some descriptive statistics to get a feeling for the data.

introduction to fundamentals of statistics

For example:. The most common descriptive statistics are in the following table, along with their formulas and a short description of what each one measures. When designing a study, the sample size is an important consideration because the larger the sample size, the more data you have, and the more precise your results will be assuming high-quality data.

If you know the level of precision you want that is, your desired margin of erroryou can calculate the sample size needed to achieve it. In statistics, a confidence interval is an educated guess about some characteristic of the population.

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A confidence interval contains an initial estimate plus or minus a margin of error the amount by which you expect your results to vary, if a different sample were taken. The following table shows formulas for the components of the most common confidence intervals and keys for when to use them.

You use hypothesis tests to challenge whether some claim about a population is true for example, a claim that 40 percent of Americans own a cellphone. To test a statistical hypothesis, you take a sample, collect data, form a statistic, standardize it to form a test statistic so it can be interpreted on a standard scaleand decide whether the test statistic refutes the claim. The following table lays out the important details for hypothesis tests.

Deborah J. Cheat Sheet. Statistics For Dummies Cheat Sheet. Understanding Formulas for Common Statistics After data has been collected, the first step in analyzing it is to crunch out some descriptive statistics to get a feeling for the data. For example: Where is the center of the data located? How spread out is the data?After you enable Flash, refresh this page and the presentation should play.

Get the plugin now. Toggle navigation. Help Preferences Sign up Log in. To view this presentation, you'll need to allow Flash. Click to allow Flash After you enable Flash, refresh this page and the presentation should play.

View by Category Toggle navigation. Products Sold on our sister site CrystalGraphics. Title: Fundamentals of Statistics. Description: frequency for 44 6 plus the frequency for 45 4. Finally, notice that the cum. Midpoint, Xi Tags: fundamentals kira plus statistics tires. Latest Highest Rated. A collection of quantitative data from a sample or population. The science that deals with the collection, tabulation, analysis, interpretation, and presentation of quantitative data.

Conclusions probability?

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It is the entire group we are interested in, which we wish to describe or draw conclusions about. For each population there are many possible samples. By studying the sample it is hoped to draw valid conclusions about population. The sample should be representative of the general population. The best way is by random sampling.

Introduction to Statistics

For example, the population mean is a parameter that is often used to indicate the average value of a quantity. Data 0.

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Analytical Summarize data by computing a measure of central tendensy and dispersion. Systematic sampling - the process of selecting every n-th member of the population arranged in a list.

Stratified sample - obtained by dividing the population into subgroups and then randomly selecting from each subgroups. Cluster sampling - In cluster sampling groups are selected rather than individuals. Incidental or convenience sampling - Incidental or convenience sampling is taking an intact group e. We wish to summarize this data by creating a frequency distribution of the temperatures.

Create a column with variable, in this case temp. Enter the highest score at the top, and include all values within the range from highest score to lowest score. Create a tally column to keep track of the scores. Create a frequency column. At the bottom of the frequency column record the total frequency. For example The cum. The IQ scores in the range 73 to To include these scores in a freq.

This would not summarize the data very much.All the same Lynda. Plus, personalized course recommendations tailored just for you. All the same access to your Lynda learning history and certifications. Same instructors. New platform. What's their first move every morning? They grab their phone. Check the time and temperature, numbers. Numbers tell us how fast to move, how warm to dress.

They help us decide where to invest our money. Numbers can motivate us to act, and that's just when the numbers are given to us. If you have the power to organize large pools of data, you have the ability to discover trends, prove yourself right, or maybe prove others wrong. This is the power of statistics.

introduction to fundamentals of statistics

Whether you're a manager or a designer, whether you're in business, science, sports or education, whether you're trying to save time, money or any other valuable resource, understanding statistics is vital if you wanna be more effective and efficient. Hi there, my name is Eddie Davila and I'm a university instructor with degrees in business and engineering. I write ebooks and of course I develop other online educational content. I'm a huge sports fan, I love to follow the entertainment industry and I'm passionate about science and health, and I can tell you that in every important facet of my life having a better understanding of statistics allows me to improve my performance and often to find a greater level of satisfaction whether I'm working or playing.

This course, Statistics Fundamentals, is the first of a three part series that I'm hoping will empower you to better understand the numbers you will encounter in your life. In this course we'll discuss basic terms like mean, median and standard deviation. We'll look at many different forms of probability.

We'll explore the power of the bell shaped normal distribution curve. We'll discuss issues like false positives, and expected monetary value, and I'll tell you even if you know what all these things are, I think you'll walk away with a new prospective.

Actually I'm hoping you'll never look at these basic concepts the same way again. You won't just understand what these numbers are and how they're calculated, you'll know their inherent weakness too. So, welcome to Statistics Fundamentals. Are you sure you want to mark all the videos in this course as unwatched?

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This will not affect your course history, your reports, or your certificates of completion for this course. Type in the entry box, then click Enter to save your note. Start My Free Month. You started this assessment previously and didn't complete it. You can pick up where you left off, or start over. Develop in-demand skills with access to thousands of expert-led courses on business, tech and creative topics.Chapter 3 : Discusses how to find where a score stands or 'ranks' within distribution and introduces.

Chapter 7 : This chapter introduces the concept of estimation and sampling and how we can use sample data to make inferences populations. Fundamental Statistics.

Search this site. About the Author. Chapter 1: Introduction to Statistics. Chapter 2: Frequency Distributions and Graphing. Chapter 3: Rankings in a Distribution. Chapter 4: Central Tendency. Chapter 5: Variability. Chapter 6: Standard Scores. Chapter 7: Estimation and Sampling Distributions. Chapter 8: Probability. Chapter 9: Binomial Probability. Chapter Introduction to Hypothesis Testing.

Chapter one Sample t-test. Chapter Bivariate Designs.

Statistics full Course for Beginner - Statistics for Data Science

Chapter Independent Groups t-Test. Chapter Paired Samples t-Test. Chapter Correlation. Chapter Regression. Chapter Introduction to Analysis of Variance. Chapter Chi-Square.

introduction to fundamentals of statistics

Chapter Power Analysis. Table 1 z-Tables. Table 2 t-Tables. Table 4 Studentized Range, q. Table 5 Chi-Square. Table 6 Fisher's r to r'. Table 7 Factorials. Appendix B: Math Review.


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