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Quantitative Specialists

November, 2019.

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November, 2019.

Get marketable and highly sought after skills in this course that will increase your knowledge of data analytics, with a focus on descriptive statistics, an important tool for understanding trends in data and making important business decisions.  

Enroll now to join the more than 2000 students and get instant access to all course content.

Whether a student or professional in the field, learn the important basics of both descriptive statistics and 

        By monitoring and analyzing data correctly, you can make the best decisions to excel in your work as well as increase profits and outperform your competition. 

        This beginner's course offers easy to understand step-by-step instructions on how to make the most of 

  Make Better Business Decisions with SPSS Data Analysis 

  • Create, Copy, and Apply Value Labels

  • Insert, Move, Modify, Sort, and Delete Variables

  • Create Charts and Graphs

  • Measure Central Tendency, Variability, z-Scores, Normal Distribution, and Correlation

  Interpret and Use Data Easily and Effectively with IBM SPSS 

        You can use it to perform every aspect of the analytical process, including planning, data collection, analysis, reporting, and deployment. 

        This introductory course will show you how to use SPSS to run analyses, enter and code values, and interpret data correctly so you can make valid predictions about what strategies will make your organization successful. 

  Contents and Overview 

        This course begins with an introduction to IBM SPSS. It covers all of the basics so that even beginners will feel at ease and quickly progress. You'll tackle creating value labels, manipulating variables, modifying default options, and more. 

        Once ready, you'll move on to learn how to create charts and graphs, such as histograms, stem and leaf plots, and more. You'll be able to clearly organize and read data that you've collected. 

        Then you'll master central tendency, which includes finding the mean, median, and mode. You'll also learn how to measure the standard deviation and variance, as well as how to find the z-score. 

        The course ends with introductory statistics video lectures that dive deeper into graphs, central tendency, normal distribution, variability, and z-scores. 

        Upon completion of this course, you'll be ready to apply what you've learned to excel in your statistics classes and make smarter business decisions. You'll be able to use the many features in SPSS to gather and interpret data more effectively, as well as plan strategies that will yield the best results as well as the highest profit margins. 

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What's inside

Learning objectives

  • Learn the basics of the spss software program, including how to enter and code values, run analyses, and interpret output
  • In this course, you will gain proficiency in how to produce and interpret a number of different descriptive statistics in spss

Syllabus

In this lecture, an overview of the course is provided, including how to access the data files and the output files.

Introduction to SPSS
Read more

An introduction to SPSS is covered in this lecture.

The SPSS data files (for the entire course) are available under "downloadable materials" (see below) in this lecture. The file labeled "Data Files Descriptive Statistics in SPSS" contains the set of data files for the course.

Also, a pdf file of the results (the output file) is also available. The output file for this lecture is located below and is titled, "Introduction output"

All other output files are located within their respective lecture.

This lecture covers how to create value labels for different categories of a variable. In SPSS, numbers are required to be entered (in nearly all circumstances) to perform analyses. Value labels help us keep track of which group corresponds to a given number such as 1 = "male" and 2 = "female".

In this lecture, how to copy value labels to multiple variables at once is illustrated. Likert scales are also explained, including how to code them in SPSS.

In this video, how to insert, move, and delete variables is illustrated. Shortcut keys are also described (including the benefits of using them).

There is no output file for this lecture, as no SPSS output is produced.

In this video, how to insert one or more cases is illustrated. “Cases” in SPSS are the rows in the data file when the Data View window is selected.

There is no output file for this lecture, as no SPSS output is produced.

This video illustrates how to use the sort command in SPSS. The sort command is illustrated first on a single variable in SPSS; afterwards, the data set is sorted on two variables simultaneously. How to sort using both ascending (lowest values first) and descending (highest values first) order is shown.

This video examines how to modify a number of different default options in SPSS, including font type, style, and size, decimal places, value labels, and gridlines in the Data View window.

In this video, we take a look at how to modify the columns that are displayed in the variable view window when SPSS is opened.

How to Edit SPSS Tables
How to Copy a Dataset

In this video, we take a look at how to save an SPSS output file as a pdf file, which can help for printing two-sided documents.

Creating Charts and Graphs in SPSS

How to create a bar chart in SPSS is covered in this lecture. Bar charts are typically created on categorical variables, such as gender, ethnicity, and so on. The bars of a bar chart are not touching (there are gaps in-between them) since the data are not continuous (they are categorical or discrete).

How to create a histogram in SPSS is covered in this lecture. Histograms are typically created on continuous variables, such as height, weight, high school GPA, and so on. Unlike the bar chart covered in the previous lecture, the bars of a histogram are touching (as long as there is a frequency of at least one for a given category) since the data are continuous.

In this video, we take a look at how to construct and interpret a boxplot in SPSS. Each of the 5 key values in the boxplot are interpreted (minimum, Q1 median, Q3, and maximum), including the effect of outliers.

How to create a stem and leaf plot is covered in this lecture. Stem and leaf plots are interesting alternatives to histograms, as they convey the same information as a histogram, while having the advantage of also presenting the actual values in the graph.

Interesting note: Unlike the bar chart and histogram, notice that the graphics for the stem and leaf plot are a bit antiquated and could use some updating!

How to create a scatterplot is covered in this lecture. Scatterplots contain one variable on the X-axis and another variable on the Y-axis. It's a good idea to create a scatterplot when conducting a correlation coefficient. Correlation is a topic covered in our next course, "Inferential Statistics in SPSS - Step by Step".

How to create a frequency distribution table is illustrated in this lecture.

How to create a pie chart and modify chart options in SPSS is illustrated in this video.

Central Tendency, Variability, z-Scores, and Correlation in SPSS

In this lecture, how to calculate the mean, median, and mode is illustrated using the frequencies procedure in SPSS.

In this lecture, how to calculate the standard deviation and variance is illustrated. The measures are obtained first using the descriptives procedure and then the frequencies procedure in SPSS.

In this lecture, how to obtain the mean and standard deviation is illustrated using the frequencies procedure in SPSS.

In this lecture, the mean and standard deviation is obtained for separate groups of a categorical variable using the means procedure in SPSS.

In this lecture, how to calculate z scores on a variable is illustrated. After calculating z scores, the mean and standard deviation on the new z-score variable is found to show that the mean of the new variable is 0 and the standard deviation is 1 (within rounding error), which is a property of the z-score distribution.

In this video, we take a look at Pearson’s r correlation coefficient. We examine it first as a descriptive statistic (the topic of this class), then we take a look at it an inferential statistic (as a preview to our next course). The basic difference between these two approaches is the following: as a descriptive statistic, correlation describes the relationship between two variables, while as an inferential statistic, we test to see whether the correlation is significantly different from zero (in addition to describing the relationship).

Statistics Videos I - Graphs and Central Tendency

This video lecture covers the mean, median, and mode. First the mode is covered, including examples of two modes (bimodal) and three or more modes (multimodal). Next, finding the median is covered for both an even and odd number of values. After the median, how to calculate the mean (arithmetic average) is covered.

Quiz - Mean, Median, and Mode

In this video, the answers to the mean, median, and mode quiz are reviewed with explanations provided. The answers are also available in the attached PDF file.

Note: On problem #5, I state, "1, 3, 3, 5", but should have stated "1, 3, 3, 3, 5."

In this video, we take a look at the relationship between the mean, median, and mode and asymmetrical (skewed) distributions. As the video illustrates, the order of the three measures of central tendency (where they fall on a number line in relation to each other) depends on whether a distribution is positively or negatively skewed.

Quiz - Central Tendency and Skewed Distributions

This video reviews the answers to the quiz on central tendency and skewed distributions. The answers are also available in the attached PDF file.

In this video, we take a look at the weighted mean, which can be used for finding an overall mean for two groups.

The Weighted Mean

In this video, the quiz answers are reviewed on the weighted mean.

In this video, we examine how to construct a cumulative frequency distribution table, which includes the columns X, f, and cf. X corresponds to the values (or scores) of a variable X, f is the frequency value for each X (how many of each X there are), and cf is the cumulative frequency.

In this video we examine how to construct a stem and leaf plot on a set of numbers ranging from the tens to fifties.

In this video, how to create a boxplot in SPSS is illsutrated.

In this video, we take a look at how to calculate percentiles in SPSS. Along with percentiles, how to interpret quartiles is also discussed.

Statistics Videos II - Variability, Normal Distribution, and z-Scores

In this video, we take a look at how to calculate the variance and standard deviation by hand. Each step and calculation is illustrated in arriving at the solutions.

Standard Deviation and Variance

This video reviews the quiz on the standard deviation and variance, illustrating step by step how to find each value.

In this video, the normal distribution and z scores are covered. First, properties of the normal distribution are described, including how the mean, median, mode are equal to zero and how the normal distribution is symmetrical. Next the areas under the curve are illustrated, closing with a demonstration of the 68, 95, 99.7 rule for values that are 1, 2, and 3 standard deviations away from the mean.

In this video lecture, we take a look at the properties of the z score normal distribution, including (1) that it is symmetrical, (2) that the mean, median, and mode are all equal to zero, and (3) that the standard deviation is equal to 1.

Properties of the z Score Normal Distribution

This video reviews the answers to the quiz, Properties of the z-Score Normal Distribution.

In this video lecture, z scores are covered, including how to solve for z scores for a number of different examples. Also illustrated is how the z score indicates the number of standard deviations a value is from the mean. For example, a z score of 1.5 indicates that a value is 1.5 standard deviations above the mean.

Solving for z-Scores
Video Review of Quiz - Solving for z-Scores

In this video, we take a look at how to solve for X given a z score, mean, and standard deviation. This not only is covered in many statistics texts, but is a very common procedure that is used in score reporting for standardized tests, such as IQ tests, the SAT, and so on. In creating these types of test scores, standard test companies have a z score for each test taker and then find their X value (for example, IQ score) using a certain mean and standard deviation (a popular one for IQ tests: mean = 100, standard deviation = 15).

Solving for X Given a z-Score

In this video, the answers are reviewed to the quiz, Solving for X Scores Given a z-Score.

Conclusion & Course Previews

In this video, the one sample t test is introduced from our Introductory Statistics in SPSS Course. In the course, several procedures are covered, including:

one sample t test (2 examples + confidence intervals and effect size)

independent samples t test (2 examples + confidence intervals and effect size)

dependent samples t test (2 examples + confidence intervals and effect size)

one-way between subjects ANOVA (2 examples + effect size)

Post hoc tests

One-way within subjects ANOVA (2 examples)

+ Post hoc tests

Correlation (2 examples)

Regression (2 examples)

Chi-square goodness of fit test (2 examples)

Chi-square test of independence (2 examples)

And more!

This video previews content from our upcoming course, Survey Data and Likert Scale Analysis. Course is now available!

Course Conclusion

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides a solid statistical grounding for students and professionals in various fields
Emphasizes hands-on application of descriptive statistics using IBM SPSS, making it practical and relevant
Covers a comprehensive range of descriptive statistics, preparing learners for further statistical analysis
Beginner-friendly approach makes it accessible to students with limited statistical knowledge
Taught by expert instructors in quantitative analysis, ensuring high-quality content
May require additional prerequisite knowledge in statistics for some learners

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Reviews summary

Well-designed spss course

learners say this Excellent training course provides a well-designed overview of SPSS and statistics.
Covers fundamental statistical concepts.
"Excellent training course design for both SPSS and statistics."
Introduces key SPSS functions.
"Excellent training course design for both SPSS and statistics."

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 Statistics/Data Analysis with SPSS: Descriptive Statistics with these activities:
Review current knowledge of descriptive statistics
Establish a strong foundation in descriptive statistics by reviewing previously learned concepts, improving your understanding of the upcoming course material.
Browse courses on Descriptive Statistics
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  • Review notes and materials from previous statistics courses or textbooks.
  • Complete practice problems and exercises to test your understanding of central tendency, variability, and normal distribution.
  • Use online resources or textbooks to refresh your memory on the basics of descriptive statistics.
Read 'Statistical Methods for the Social Sciences' by Frederic S. Lane
Expand your understanding of statistical methods by reading a comprehensive textbook, gaining insights from a different perspective and reinforcing the concepts covered in the course.
Show steps
  • Obtain a copy of the book.
  • Read the chapters relevant to the course topics.
  • Take notes, highlight key concepts, and summarize the main ideas.
  • Complete the exercises and problems provided in the book.
Organize and synthesize course materials and resources
Enhance your understanding and retention of course materials by organizing and synthesizing them, creating a comprehensive and personalized resource for future reference.
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  • Gather all course materials, including lecture notes, slides, assignments, and readings.
  • Review and organize the materials by topic or concept.
  • Create summaries, diagrams, or mind maps to connect and synthesize the information.
  • Add additional notes or insights from your own research or understanding.
Five other activities
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Show all eight activities
Engage in peer-led study groups or discussions
Enhance your learning through collaborative discussions with peers, fostering a deeper understanding of the course material and diverse perspectives.
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  • Form or join a study group with classmates.
  • Meet regularly to discuss course concepts, share insights, and work through problems collectively.
  • Prepare questions and topics for discussion to guide your sessions.
  • Take turns leading the discussions and presenting your understanding.
Explore online tutorials on SPSS software
Become familiar with the SPSS software by following guided tutorials, enhancing your ability to apply the statistical concepts learned in the course to real-world data analysis.
Browse courses on SPSS
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  • Search for online tutorials or video demonstrations on SPSS.
  • Follow the instructions in the tutorials to learn how to navigate the software, enter data, and perform basic statistical analyses.
  • Complete the exercises and practice problems provided in the tutorials.
  • Experiment with different SPSS features and functions to gain hands-on experience.
Complete practice exercises on descriptive statistics concepts
Solidify your understanding of descriptive statistics concepts by engaging in targeted practice exercises, improving your problem-solving skills and confidence in applying statistical techniques.
Browse courses on Descriptive Statistics
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  • Find practice exercises and problem sets from textbooks, online resources, or the course materials.
  • Work through the exercises step-by-step, applying the concepts and formulas you have learned.
  • Check your answers against provided solutions or consult with classmates or instructors for guidance.
  • Repeat the exercises with different datasets to reinforce your understanding.
Attend workshops on statistical analysis or SPSS software
Enhance your knowledge and skills by attending workshops led by experts in statistical analysis or SPSS software, gaining practical insights and hands-on experience.
Browse courses on Statistics
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  • Research and identify workshops that align with your learning goals.
  • Register for the workshops and attend the sessions.
  • Actively participate in the workshops, ask questions, and engage with the instructors and other attendees.
  • Apply the knowledge and techniques learned in the workshops to your course assignments and projects.
Develop a data analysis project using SPSS
Apply your knowledge of descriptive statistics and SPSS software by undertaking a hands-on data analysis project, fostering your analytical thinking and problem-solving abilities.
Browse courses on SPSS
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  • Choose a dataset and research question that aligns with the course topics.
  • Use SPSS to import the data, clean it, and perform descriptive statistical analyses.
  • Interpret the results of your analyses and draw meaningful conclusions.
  • Create a report or presentation to showcase your findings and insights.

Career center

Learners who complete Statistics/Data Analysis with SPSS: Descriptive Statistics will develop knowledge and skills that may be useful to these careers:
Statistician
Statisticians collect, analyze, interpret, and present data. This course in descriptive statistics provides a solid foundation for this role, as it introduces the principles of data analysis, statistical inference, and modeling. You'll learn how to use statistical software to analyze data, develop models, and make predictions. This knowledge is essential for Statisticians, who need to be able to provide data-driven insights to organizations.
Quantitative Analyst
Quantitative Analysts use statistical and mathematical modeling to solve complex business problems. This course in descriptive statistics provides a strong foundation for this role, as it introduces the principles of data analysis, statistical inference, and modeling. You'll learn how to use statistical software to analyze data, develop models, and make predictions. This knowledge is essential for Quantitative Analysts, who need to be able to provide data-driven insights to businesses.
Data Analyst
Data Analysts are in high demand as organizations seek to leverage data for competitive advantage. This course is an excellent starting point for aspiring Data Analysts, as it provides a comprehensive introduction to descriptive statistics, data visualization, and statistical analysis. You'll gain proficiency in using IBM SPSS, a leading data analysis software, to explore and analyze data. This course will also enhance your problem-solving and critical thinking skills, essential for success as a Data Analyst.
Business Intelligence Analyst
Business Intelligence Analysts play a crucial role in data-driven decision-making within organizations. This course in descriptive statistics provides a solid foundation for success in this field by equipping you with the skills to analyze and interpret data effectively. You'll learn techniques for summarizing and presenting data, as well as how to identify trends and patterns. This knowledge is essential for BI Analysts, who need to be able to extract meaningful insights from data to help businesses make informed decisions.
Big Data Analyst
Big Data Analysts manage and analyze large datasets to extract valuable insights. This course in descriptive statistics provides a foundation for this role, as it introduces the principles of data analysis and statistical modeling. You'll learn how to use statistical software to analyze data, develop models, and make predictions. This knowledge is essential for Big Data Analysts, who need to be able to extract insights from large and complex datasets.
Survey Researcher
Survey Researchers design, conduct, and analyze surveys to collect data on a variety of topics. This course in descriptive statistics provides a strong foundation for this role, as it introduces the principles of survey design, data collection, and analysis. You'll learn how to develop questionnaires, collect data, and analyze results to gain insights into the opinions and behaviors of a population.
Market Research Analyst
Market Research Analysts play a vital role in understanding consumer behavior and market trends. This course in descriptive statistics will equip you with the skills to collect, analyze, and interpret data to gain valuable insights into customer needs and preferences. You'll learn how to design and conduct surveys, analyze qualitative and quantitative data, and present your findings effectively. This knowledge is crucial for Market Research Analysts, who need to be able to provide actionable insights to businesses.
Data Scientist
Data Scientists use data analysis techniques to solve complex problems and make predictions. This course in descriptive statistics provides a foundation for this role, as it introduces the principles of data analysis and statistical modeling. You'll learn how to use statistical software to analyze data, develop models, and make predictions. This knowledge is essential for Data Scientists, who need to be able to extract insights from data and make informed decisions.
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. This course in descriptive statistics provides a foundation for this role, as it introduces the principles of data analysis and statistical modeling. You'll learn how to use statistical software to analyze data, develop models, and make predictions. This knowledge is essential for Machine Learning Engineers, who need to be able to build and deploy models that can learn from data and make predictions.
Operations Research Analyst
Operations Research Analysts use data analysis techniques to improve the efficiency and effectiveness of business processes. This course in descriptive statistics provides a solid foundation for this role, as it introduces the principles of data analysis and statistical modeling. You'll learn how to collect, analyze, and interpret data to identify areas for improvement and develop solutions to operational problems. This course will also enhance your analytical and problem-solving skills, essential for success as an Operations Research Analyst.
Risk Analyst
Risk Analysts assess and manage risks for organizations. This course in descriptive statistics is beneficial for this role, as it provides a foundation in data analysis and statistical modeling. You'll learn how to collect, analyze, and interpret data to identify and quantify risks. This knowledge is crucial for Risk Analysts, who need to be able to provide insights into potential risks and develop strategies to mitigate them.
Financial Analyst
Financial Analysts use data analysis techniques to evaluate investments and make recommendations. This course in descriptive statistics is beneficial for this role, as it introduces the principles of data analysis and statistical modeling. You'll learn how to use statistical software to analyze data, develop models, and make predictions. This knowledge may be helpful for Financial Analysts, who need to be able to analyze financial data and make sound investment decisions.
Actuary
Actuaries use mathematical and statistical techniques to assess risk and uncertainty. This course in descriptive statistics may be helpful for this role, as it introduces the principles of data analysis and statistical modeling. You'll learn how to use statistical software to analyze data, develop models, and make predictions. This knowledge may be beneficial for Actuaries, who need to be able to assess risk and make informed decisions.
Operations Manager
Operations Managers oversee the day-to-day operations of businesses. This course in descriptive statistics may be helpful for this role, as it introduces the principles of data analysis and statistical modeling. You'll learn how to use statistical software to analyze data, develop models, and make predictions. This knowledge may be beneficial for Operations Managers, who need to be able to analyze data to improve efficiency and productivity.
Project Manager
Project Managers plan and execute projects. This course in descriptive statistics may be helpful for this role, as it introduces the principles of data analysis and statistical modeling. You'll learn how to use statistical software to analyze data, develop models, and make predictions. This knowledge may be beneficial for Project Managers, who need to be able to analyze data to track progress and identify potential risks.

Reading list

We've selected six 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 Statistics/Data Analysis with SPSS: Descriptive Statistics.
Provides a comprehensive introduction to statistical analysis using IBM SPSS Statistics, covering all of the basics that students need to know.
Provides a hands-on approach to data analysis using SPSS, providing step-by-step instructions for performing a variety of statistical analyses.

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