Data Attributes and Similarity Measures: Exercises
Data Attributes Classification and Analysis
Exercise 1: Attribute Types
Classify the following attributes as binary, discrete, or continuous. Also, classify them as qualitative (nominal or ordinal) or quantitative (interval or ratio). Briefly indicate your reasoning if there may be some ambiguity.
- Time in terms of AM or PM.
Binary, qualitative, ordinal. - Brightness as measured by a light meter.
Continuous, quantitative, ratio. - Brightness as measured by people’s judgments.
Discrete, qualitative, ordinal.
Statistical Measures: Location, Variance, and Probability
Measures of Location
Minimum: Smallest number in the data set.
Maximum: Largest number in the data set.
Median: The middle number, or the average of the two middle numbers if the data set has an even number of values.
Mean: The average of all numbers in the data set.
Mode: The most frequent number. A data set can have multiple modes.
Quartiles
First Quartile (Q1): The median of the lower half of the data.
Third Quartile (Q3): The median of the upper half of the data.
Measures of Variance
Range: Maximum –
Read MoreAccounting, Studies, Experiments, Distribution, and Intervals
Fund Accounting
Fund accounting is a method of accounting used by a nonprofit organization that illustrates accountability, rather than profitability. In a business, you want to know how much was spent, how much was earned, and how much was left over. With a nonprofit, you want to know these things, but you also want to make sure that the money you have, receive, and spend is allocated for the proper purpose. Fund accounting is very detailed and can get confusing, but ultimately it is the most accurate
Read MoreKey Statistical Concepts and Hypothesis Testing
Multiple Choice Section
- If p is greater than alpha in a hypothesis test, do not reject the null hypothesis.
- The form of a relationship determines the effect of the independent variable (IV) on the dependent variable (DV).
- Degrees of freedom for chi-square: (rows – 1) x (columns – 1)
- ANOVA compares the means of more than 3 groups. A t-test compares 2 groups.
- The direction of a relationship between two interval/ratio variables depends on the sign of r and b.
- The significance of a relationship determines
Key Concepts in Statistical Sampling and Analysis
Key Concepts in Statistical Sampling and Analysis
Sampling and Population
- Which of the following is not an advantage of using a sample versus a census?
Ready access to respondents. - Which of the following refers to the basic level of investigation?
A sample unit. - Which of the following describes an entire group under study as specified by the objectives of the research project?
Population. - Of the following, which is not true of nonprobability samples?
Can compute the chances of any one population member
Statistical Concepts and Methods
Module 1: Core Statistical Concepts
Parameters and Statistics
A parameter summarizes a population (e.g., mean, median, standard deviation). Parameters are constant but usually unknown. A statistic is calculated from a sample (e.g., sample mean) and used to estimate parameters. Statistics are random and depend on the sample.
Point Estimates
A point estimate is a sample value used to estimate a specific population parameter. For instance, the sample mean can be a point estimate for the population mean.
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