Linear Regression Analysis Paper

2. Based on the scale of measurement for each variable listed below, which measure of central tendency is most appropriate for describing the data?

As discussed in the previous section, a normal distribution has particular characteristics it conforms to. i.e.

The coefficient of variation (CV) represents a percentage of standard deviation to the mean and can be calculated by dividing the standard deviation calculated using Equation 2 by the expected value. The equation can be calculated by:

Standard deviation is important in comparing two different sets of data that has the same mean score. One standard deviation may be small (1.85), where the other standard deviation score could be quite large (10)(Rumsey,

5. Give the standard deviation for the mean and median column. Compare these and be sure to identify which has the least variability?

5. Give the standard deviation for the mean and median column. Compare these and be sure to identify which has the least variability?

The coefficient of variation is in the “fair” range for data consistency, for all quartiles except the top quartile which is in the “good” range. (Gardner, 2012)

1. What unit of measurement is used to describe how far a set of values are from the mean? 2. Explain how to standardize a value. 3. Briefly describe why standardized units are used to compare values that are measured using different scales, different units, or different populations. 4. How does adding or subtracting a constant amount to each value in a set of data affect the mean? Why does this happen? 5. How does multiplying or dividing a constant amount by each value in a set of data (also called rescaling) affect the mean? Why does this happen? 6. How does adding or subtracting a constant amount to each value in a set of data affect the standard deviation? Why does this happen? 7. How does multiplying or dividing a constant amount by each value in a set of data (also called rescaling)

Based on the given sample of student test scores of 50, 60, 74, 83, 83, 90, 90, 92, and 95 after rearranging them from least to greatest. As the mean is based on the average of sum, the average of this sample is 79.67 or 80. The mode refers to numbers that appear the most in a sequence and in this case 83 and 90 both appear twice. Range calculates the difference between the largest and smallest number, which are 95 and 50 which have a difference of 45. The variance is the difference between the sum of squares divided by the sample size, which is the number in the sample minus one (Hansen & Myers, 2012), meaning it takes each number of the set and subtracts

10. Using measures of center and measures of variability compare the number of credit hours students in this sample are taking and the number of hours watching television.

It is one of the most popular and well known measures of central tendency. It can be used with both discrete and continuous data, although its use is most often with continuous data

Statistical dispersion is measured by a number system. The measure would be zero, if all the data were the same. As the data varies, the measurement number increases. There are two purposes to organizing this data. The first is to show how different units seem similar, by choosing the proper statistic, or measurement. This is called central tendency. The second is to choose another statistic that shows how they differ. This is known as statistical variability. The most commonly used statistics are the mean (average), median (middle or half), and mode (most frequent data). After the data is collected, classified, summarized, and presented, then it is possible to move on to inferential statistics if there is enough data to draw a conclusion.

First of all it is worth to take a look at any outliers that may affect a distribution of the data.

These represent the range of the sale price. Lastly, I used the formula to get the standard deviation 48,945.28, which measures the variability.

In statistics, variance refers to the comparison of the means of more than two groups. The term "variance may mislead some students to think the technique is used to compare group variances. In fact, analysis of variance uses variance to cast inference on group means...Whether an observed difference between groups mean is 'surprising' will depends on the spread (variance) of the observations within groups. Widely different averages can more likely arise by chance if individual observations within groups vary greatly" (Analysis of variance. 2012, Stat Primer). Variances indicate the presence of change or the existence of a statistically significant difference between two groups being compared.