Applied Statistical Inference with MINITAB by Sally A Lesik

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Description :

Statistical inference involves gathering and analyzing data to answer an important meaningful question. For example, a researcher in education may want to know whether the use of computers in an algebra classroom was effective in helping students build their mathematical skills. A psychology researcher may want to know if children who play violent video games have more disturbing thoughts than children who do not play violent video games. In other fields, such as environmental science, researchers may want to learn what factors contribute to global warming by asking questions such as what types and models of cars emit the most amounts of greenhouse gases.

Once the researcher describes the problem he wishes to investigate, he will proceed to collect or define a set of data that consists of information about a variable or variables of interest. There are two basic types of data that can be collected, quantitative data and qualitative data.

Quantitative data are numeric in figure. The main purpose of collecting quantitative data is to describe some phenomena using numbers. For example, quantitative data can be collected to assess the impact of advertising on total product sales.

On the other hand, the qualitative data are categorical in nature and describe some phenomena using words. For example, qualitative data can be used to describe what the learning environment looks like in a particular math classroom by using words to describe the types of student-teacher interactions and how students appear to participate in learning.