lecture 1

lecture 1 - Descriptive Statistics Everything dealing with...

This preview shows pages 1–10. Sign up to view the full content.

Descriptive Statistics

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Everything dealing with collection, processing, analyzing, and interpretation of numerical data belongs to the domain of statistics . Statistics as a science develops statistical ideas from its probabilistic foundation, and applies them in the different fields of science and practice.
Once the data have been obtained, we may organize and summarize them in such a way as to arrive at their orderly presentation. Such procedures are often termed descriptive statistics. For example, tabulation might be made of the heights of all university students, indicating an average height for each age.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
However, we may want to make some generalizations from these data. We may wish to conclude whether university males are on average taller than females. The ability to make such generalized conclusions, inferring characteristics of the whole from characteristics of its parts, lies within the realm of inferential statistics or inductive statistics.
Types of Data and Variables Whenever we make an observation on a variable for some collection of individuals or objects, we call the results a data set . 1. Data on a Nominal (Categorical) Scale If we determine the car color for each of 5 cars and the results are grey, blue, red, brown, and black the collection of these 5 observations is a categorical or nominal data set . The order of listing the categories is irrelevant.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
2. Data on an Ordinal (Rank-order) Scale Numbers represent rank-orders , and do not give information regarding the differences between adjacent ranks. The characteristics can be put into categories but the categories can also be ordered. E.g., patient condition (good, fair, serious, critical), attitude scale (1=Strongly agree, 2=Agree, 3=Neutral, 4=Disagree, 5=Strongly disagree). Ordinal variables can order categories, but distances between categories are unknown.
3. Data on an Interval Scale When objects or events can be distinguished from one another and ranked, and when the differences between measurements also have meaning, the interval scale of measurement is applicable. An interval variable is one that does have numerical distances between any two values. In a Fahrenheit thermometer, mercury rises in equal intervals called degrees.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
However, the zero point is arbitrary, chosen simply because Fahrenheit decided that the zero point on his scale would be 32° below the freezing point of water. Because the units are in equal intervals, it is possible to add and subtract across an interval scale. You can say that 100°F is 50° warmer than 50°F, but you cannot say that 100°F is twice as hot as 50°F because zero does not represent the complete absence of heat.
4. Data on a Ratio Scale The zero point for these variables is not arbitrary but determined by nature so it is possible to multiply and divide across a ratio scale.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

What students are saying

• As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

Kiran Temple University Fox School of Business ‘17, Course Hero Intern

• I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

Dana University of Pennsylvania ‘17, Course Hero Intern

• The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

Jill Tulane University ‘16, Course Hero Intern