mean, median, mode, variance, standard deviation, skewness, and kurtosis.

Transcription

1 Quantitative Methods Assignment 2 Part I. Descriptive Statistics 1. EXCEL Download the Alabama homicide data to use in this short lab and save it to your flashdrive or to the desktop. Pick one of the variables and make a table to display the following statistics. mean, median, mode, variance, standard deviation, skewness, and kurtosis. As always, there are multiple ways to perform tasks in Excel. Highlight the variable of interest. You may construct a pivot table and edit your field settings to display the information. You may also use the statistics formulas under the Formula tab (see below), or you may also use the Insert function button and drop down menu in the upper left corner. In Excel 07 it is a matter of finding the correct submenu. Now that you have constructed your table, make a graph of the raw data and place the y axis crossing at the value of the mean (click on format axis and simply change it to the mean).

2 2. SPSS IN SPSS descriptive statistics can be performed much more efficiently than EXCEL. It also constructs tables for you so you can easily find the same values as you did in Excel. mean, median, mode, variance, standard deviation, skewness, and kurtosis. Import the homicide file into SPSS. There are several options for performing a variety of descriptive analyses simultaneously. I recommend either of the following. Under the Analyze tab< Descriptive Statistics< frequencies or < Descriptive Statistics <explore. Frequencies is less detailed and explore might overload you. Both will get the job done. Under the Analyze tab< Descriptive Statistics< frequencies you should see a window with this appearance. Move % Gun, % Knife, and % Other weapons to the variable field. Check Display Frequencies in the lower left corner Click the statistics button and check almost everything (see example).

3 Next click on the charts button and check Histogram with normal distribution and then hit continue and then OK. Please copy and paste the first Statistics Output box into your assignment along with the histograms.

4 3. OFF WEEK PROJECT ASSIGNMENT Provide the following information Possible Title Central Research Question/ Hypothesis Primary data sources List websites or other sources of information Size of your dataset (row x column or megabytes) Likely statistical procedures to be employed (use handout and take a guess) Time Budget Part II. Normality and Standardization Open the large SPSS file titled Eneb2. In this assignment you will test for normality using descriptive statistics, visual tests, and statistical tests. You will also perform a log transformation of the data and retest for normality. The Eneb2 file is characterized by a variable field (var 00001) with 11 variables. These are weather stations in eastern Nebraska. There are several other variables listed but we are concerned with Precipitation (Pre). Since there are ~94K rows of data, you should select cases to trim the dataset to improve processing speed. As you learned in week 1, filter the Precip data using m=5 (month = may). Now, Go to Analyze<Descriptive Statistics<Explore. Click the Plots button. Uncheck Stem and leaf and check Normality Plots with tests.

5 Paste your output into your assignment. Please include the descriptive box, test of normality, histogram, and Q Q plot. Evaluate the hypothesis that the data is normal and discuss your findings. Remember Ho: The distribution of the data is normal Ha: The distribution of the data is not normal Example: Tests for normality were performed using Visual methods in conjunction with a Kolmogorov Smirnov test of normality There is sufficient evidence to reject/fail to reject Ho (and report values) Next, Filter the cases by M = 5 & pre >.01. This eliminates the excessive 0 value days and trims the dataset to only days that experienced measurable precipitation. Repeat the same procedures. You do not have to paste the tables and graphs but please evaluate the assumption of normality compared to your previous output. What has changed? Is the data normally distributed? Now, change the filtered precip data (m=5&pre>.01) into Z scores. Under Analyze<Descriptive Statistics<Descriptives, check the box in the bottom left that says save standardized values as variables.

6 A new variable will be created titled ZPre. Under Descriptive statistics go to explore and place ZPre in the dependent field. Now you have eliminated 0 value days and transformed the resulting precipitation into Z scores. Has anything changed regarding the distribution? Next, delete the Zpre field and save the eneb2 data file with your filter to the desktop. Perform a logarithmic transformation of the same filtered data M = 5 & pre >.01. Once you perform the log transform, the precip data will be converted into a new variable. Under Transform<Compute Variable Change Pre into LN(pre). Type Pre into the box in the upper left corner and click on the type and label button. Click on the use expression as variable button.

7 Repeat the same procedures to evaluate normality and paste the log transformed histogram, Q Q plot and Kolmogorov Smirnov test for normality. You may also want to plot the normal curve on your histogram. Is the data normally distributed after the log transformation? How would you proceed from here?