Lab 3: Descriptive Statistics

Complete the following tasks using SPSS. Print out the outputs and submit in print. For questions you need to answer, write down the answers on the printed outputs by the table or graph.

Problem Set 1

Download the dataset “heights.sav”.

1. Follow the directions below to create value labels for variable gender: 0 = male, 1 = female.

   Variable ViewàValuesàFor each different value, enter the value and label and then click Add, after all pairs are defined, click OK.

2. Follow the directions below to create a frequency table for gender. How many males and females are there in the sample and what are the corresponding proportions?

   AnalyzeàDescriptive StatisticsàFrequenciesàVariable(s): GENDERà Make sure below the boxes “Display frequency tables” is checkedàOK.

3. Follow the directions below to select all of the male cases.

   DataàSelect CasesàIf condition is satisfiedàIf...àSelect GENDER into the box on topàclick “=” and then click “0”àContinueàOK

4. Follow the directions below to find the following for the height of males in the dataset: mean, standard deviation, variance, max, min, range. What is the relationship between standard deviation and variance?

   AnalyzeàDescriptive StatisticsàDescriptivesàVariable(s): HEIGHTà Options...àCheck all items required aboveàContinueàOK.

5. Create a histogram for the heights of males. Describe the shape of the distribution.

6. Select all cases. Then follow the directions below to create a boxplot graph to compare the distribution of heights for the two gender.

   GraphsàLegacy DialogsàBoxplotàChoose Simple and Summaries for groups of cases à Variable: HEIGHT; Category Axis: GENDER à OK.

7.  Follow the directions below to explore the dataset. Produce the following output for height for each gender: means, medians, standard deviations, min, max, range, quartiles (Q1, Q2, Q3), interquartile range, extreme values, boxplots, stem-and-leaf plots, and histograms. Interpret the results.

   AnalyzeàDescriptive StatisticsàExploreàDependent List: HEIGHT; Factor List: GENDERàPlay with the specification dialogue boxes to get all items required aboveàOK. 

이번 시간에는 데이타를 가지고 그래프 (Data Visualization)를 만들어 봅시다.

Complete the following tasks using SPSS. (SPSS를 이용해서 다음 두 셋의 문제를 푸세요), 예시 파일은 맨 아래 있어요. 

Problem Set 1

“sharks.sav” 파일을 열고 데이터를 확인하세요. 데이터는 2000-2010년까지 여러 지역에 걸쳐 나타난 상어의 숫자를 나타냅니다. (Agresti & Franklin (3/e) Section 2.1 Example 2 (p.26)).

1. 디렉션을 따라서 기본 바 그래프를 만들어봅시다. 

   GraphsàLegacy DialogsàBaràChoose Simple and Values of individual casesàBars Represent: No_Attack; Category Labels: Variable: Region; Create a titleàOK

2. 1번에서 만든 바는 오른쪽에 빈 공간들이 보입니다. 데이터에 보면 데이터셋에 빈 데이터가 있는 가로줄이 있기 때문입니다. 다음 디렉션을 먼저 따라한 후 1번 작업을 다시 해 보세요. 

   DataàSelect CasesàBased on time or case rangeàRangeàEnter the first case and the last caseàOK

   만들어진 그래프를 더블클릭하면 그래프 에디터가 나오는데 여기에서 더 보기 좋은 퀄러티의 그래프를 만들 수 있습니다. 

3. Pareto version 의 바그래프를 만들려면 다음 디렉션을 따라하세요.  

   DataàSort CasesàSort by: No_Attack; DescendingàOK  

      2번과 1번 작업을 다시 실행합니다. 
      

• world-wide vs. Florida 를 비교하기 위한 clustered bar graph 를 만들어보세요. 

GraphsàLegacy DialogsàBaràChoose Clustered and Values of individual casesàBars Represent: No_Attack; Category Labels: Variable: Region; Create a titleàOK

Problem Set 2

sharks.sav

fla_student_survey.sav

Labs_answers.pdf