• Unit 2: Data Analysis

    Did you know that we analyze data every day? Think about it. Imagine a scenario where you went out last weekend and swiped your debit card to pay for lunch with friends. Then, you went shopping for a new phone and swiped your debit card again. Finally, you took your family out for a late-night movie and swiped your debit card again. The following Monday, you attempted to pay your electric bill but didn't have enough money in your account. What would you do first? You would meticulously review your account data and look at all transactions made before and after your weekend, right? You would also analyze the data to determine when, where, and how your account reached a negative balance. Reviewing debit card transaction data and analyzing when, where, and how much money was spent provides facts and insights that help you answer the question, "Why didn't I have enough money to pay my electric bill?" This is data analysis, albeit on a small scale. Data analysis enables one to draw meaningful facts and insights from data to answer specific questions. In this unit, you will learn more about data analysis, including how to determine data analysis questions and the purpose of analysis, how to collect and cleanse data in preparation for analysis, how to analyze data using specific methods and models, and how to interpret and synthesize your data analysis findings.

    Completing this unit should take you approximately 6 hours.

    • Upon successful completion of this unit, you will be able to:

      • identify and define data analysis methods and models;
      • differentiate data analysis methods and models;
      • classify data analysis findings;
      • evaluate data analysis findings;
      • summarize data analysis findings; and
      • apply newly learned knowledge, skills, and abilities to real-world datasets.

    • 2.1: Data Analysis Methods and Models

      • Introduction to Analytics Page

        Analytics is the discovery, interpretation, and communication of meaningful patterns in data. Read this article to examine the different types of analytics, their uses, and inherent challenges in the use of analytics.

      • The Stages of Analytics Development Page

        Watch this video to learn the stages of analytics development and the types of questions that you can answer at each stage. When you finish, choose an industry and identify a question you can answer in each stage.

      • Quantitative Methods Page

        Quantitative data represents items that can be counted or measured in numerical terms. Read this article to learn different types of quantitative research, the steps involved in performing the research, and the expected outcomes of quantitative methodologies.

      • Qualitative Methods Page

        Qualitative data represents items that describe or categorize attributes. Read this article to learn different types of qualitative research, the steps involved in performing the research, and the expected outcomes of qualitative methodologies.

      • Quantitative and Qualitative Data Page

        Qualitative and quantitative data have distinct characteristics. Read this article and pay attention to how the chart differentiates quantitative and qualitative data. Then, answer the example questions to evaluate your ability to recognize these differences.

      • Statistical Language Page

        Read this article to further examine the differences between quantitative and qualitative data.

      • By now, you should understand the differences between quantitative and qualitative data. Identifying the proper data type is essential to ensure your collection methods meet the business' objectives and goals.

        Quantitative versus Qualitative Data

        Quantitative Data
        		Qualitative Data
        Definition Quantitative data are the result of counting or measuring attributes of a population.
        		 Qualitative data are the result of categorizing or describing attributes of a population.
        Data that you will see
        		 Quantitative data are always numbers.
        		 Qualitative data are generally described by words or letters.
        Examples Amounts of money you have
        Height
        Weight
        Number of people living in your town
        Number of students who take statistics
        		Hair color
        Blood type
        Ethnic group
        The car a person drives
        The street a person lives on
      • The Difference between Qualitative and Quantitative Page

        Watch this video on qualitative and quantitative data. Pay attention to the approaches to each type of data and the researcher's role in recognizing quantitative and qualitative data.

      • Qualitative and Quantitative Research Page

        Watch this video on qualitative and quantitative research. Can you identify the characteristics of qualitative and quantitative data?

      • Data-Driven Decisions Page

        Our personal and professional daily decisions are based on data from many sources. Businesses have been tapping into this resource for years to determine everything from who will most likely buy a product to who they should hire. Watch this video to explore how a culture of data helps organizations make more informed and more accurate decisions to utilize their resources better.

      • Research Design Book

        Sociologists have used qualitative research methods to conduct research and obtain data to explain, predict or control an aspect of social reality. These research methods are increasingly being used in the business world to examine and explain consumer behavior and other social interactions that may impact a business. Read this article to explore the goals, sources, and primary methods used in qualitative research.

    • 2.2: Synthesizing Data Findings

      • Measures of the Center of the Data Page

        Understanding the data is the first step in analyzing the data. The mean, mode, and median are easy tools to better understand what's in the data. Read this article which defines mean, mode and median and shows how they are calculated.

      • Frequency, Frequency Tables, and Levels of Measurement Page

        Frequency is the number of times an event or a value occurs in a dataset. A frequency table lists each item and the number of times the item appears. Read this module on frequency, frequency tables, and the levels of measurement (nominal, ordinal, interval, and ratio scales). Pay attention to each frequency table exercise. After each exercise, use the definitions to identify and explain its level of measurement.

      • Frequency Tables Page

        Watch this video on collecting data into frequency tables. Focus on how to collect, tally, and display data. Take notes and use what you learned to answer each question in the video.

    • Study Guide: Unit 2

      We recommend reviewing this Study Guide before taking the Unit 2 Assessment.

    • Unit 2 Assessment

      • Unit 2 Assessment Quiz
        Receive a grade

        Take this assessment to see how well you understood this unit.

        • This assessment does not count towards your grade. It is just for practice!
        • You will see the correct answers when you submit your answers. Use this to help you study for the final exam!
        • You can take this assessment as many times as you want, whenever you want.