# Data

by Raywat Deonandan, PhD
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Slides 13 Data Epidemiology.pdf
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Hello and welcome to epidemiology. You know sometimes my clients or my research partners bring data they've already collected to me and ask me to analyze it and the problem is they've arranged the data or collected it in such a way that is not really useful or amenable to easy analysis. So today we're going to learn about data and data analysis and some of the concepts underlying data. So after today's lecture, you're going to understand the limitations of quantifying data. You're going to be able to identify the different types of measurement that a variable can embody and again variables make up our data. You're going to know why the normal curve is important in statistics. And you're going to understand the difference between type I and type II error, also a fundamentally important concept in statistics and data analysis. So let's begin by asking the question, what is measurement? What do you think measurement is? You measure things all the time, you measure your weight, you measure your height, maybe you measure certain qualities of a patient's blood sample. Measurement is when we assign a quantity to a quality, ultimately there is a quality we're trying to assess or learn about, and we quantify it in order to do math on it. So a value that may change within the scope of a problem is a variable. That's what a variable is, it is something that is changing all the time as opposed to a constant, there are constants in life, there are variables in life. Data analysis is all about processing the relationship between variables and constants between each other. So in the world of mathematics a variable can be written as X, it's a place keeper, it's just a registry that we later fill...

The lecture Data by Raywat Deonandan, PhD is from the course Data. It contains the following chapters:

• Measurement
• Levels of Measurement
• Distribution
• Type I and Type II Errors
• Learning Outcomes

1. Nominal
2. Ordinal
3. Ratio
4. Interval
1. Ordinal
2. Nominal
3. Ratio
4. Interval
1. Median
2. Mean

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