AEM 201 1st Edition Lecture 1Current LectureI. Introduction to Data and StatisticsII. Types of DataIII. Levels or Scales of Data MeasurementIntroduction to Data and Statistics- Measurement: process of transforming something our senses can’t perceive into something theycan perceive- Data: measurements that are collected, recorded, and summarized for presentation, analysis, and interpretation- Element: an entity or object on which data are collected (also called case or individual)- Variable: characteristic of the elements whose value may differ from element to element and is of interest to the data collector- Observation: measurement of a variable or variables on a single elementTypes of Data- Qualitative (Categorical) Data: data that can be grouped by specific categories- Quantitative Data: data that uses numerical values to indicate how much or how manyo Tells us more than qualitative datao Discrete: gaps between consecutive valueso Continuous: no gaps between consecutive valueso Continuous data is always larger- Data can be split up into either qualitative or quantitative. Quantitative data can be further split into discrete or continuous- One can summarize data by reporting the average, mean, median, or modeLevels or Scales of Data Measurement- Levels/Scales of Data Measurement: categorization of the values of a variable according to the amount of information conveyed about the elements to which they correspond- Nominal Level/Scale: when the data for a variable consists of labels (can be numerical or non-numerical)These notes represent a detailed interpretation of the professor’s lecture. GradeBuddy is best used as a supplement to your own notes, not as a substitute.- Ordinal Level/Scale:data exhibits the properties of nominal data and in addition, the order or rank of the data is meaningful (can be numerical or non-numerical code)- Interval Level/Scale:data has all the properties of ordinal data and in addition, the interval between values is expressed in terms of a fixed unit of measure- Ratio Level/Scale:data has all the properties of interval data and the ratios of two values are meaningful. Requires that the data has a zero value that indicates that nothing exists for the variable at point
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