We can also consider Yes / No questions, such as “Does your family live within 1 kilometer from school?” categorical data. A student’s preferred sport, gender, hair color, or eyes are categorical data. On the other hand, categorical data describe groups. We can count, measure, and add years and kilograms because this is numerical information. Numerical data are expressed in numbers, which can be measured-for example, students’ age, height, and weight. In the questionnaire, students were asked to provide two data types: numerical and categorical. They can allow us to make informed inferences about the whole population. Had the teacher been able to collect data from all students in the class, then the data would be from the entire population.Ī population includes every member of a group we’re interested in, while a sample is a smaller group taken from that population.Įven though sometimes-as in this case-we cannot collect data for the entire population, sample data can be beneficial. When the available data is limited, we say it’s a sample. The teacher realized they would not have data on the entire class. For various reasons, only 31 students submit their questionnaires. Suppose a cooking class teacher asks all 36 students to complete a questionnaire at the beginning of the year. To illustrate statistical concepts understandably, let’s provide an example. We start with familiar terms like population and mean, then define the more complex-sounding (but still basic) ones like kurtosis and dispersion. Our Basic Statistics Crash Course aims to help you grasp essential statistical concepts. Any field that uses data involves statistics. It allows individuals and organizations to make informed decisions and derive data-driven insights. Statistics has numerous applications in science and business. They form hypotheses and use statistical methods and models to test them, draw conclusions, and make predictions. Statisticians gather data through surveys, experiments, and observations. Statistics concerns the collection, analysis, interpretation, and representation of data.
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