Minitab Lab #2 – Entering and Manipulating Data

 1. Background Information for the Big Mountains Data

All 14 of the world’s 8,000-meter peaks are located in the Himalaya or the Karakoram ranges in Asia. To reach the summits of all 14 is considered to be one of the greatest feats in mountaineering. Italian climber Reinhold Messner was the first person to accomplish this feat, doing so between 1970 and 1986.

2. The Big Mountains Data

At the end of the lab (Section #16) is a list of the fourteen 8,000 meter peaks. Heights are given in feet and they are listed in the chronological order of their first summits.

3. Entering the Data into Minitab

    1. Enter the names of the mountains in the order above into the first column of a Minitab worksheet. The column name will change from C1 to C1-T once text is entered in that column – the T stands for text format. Label the column "Mountains" in the cell directly above the first mountain name you had entered.  Note: The small arrow in the upper left corner of the worksheet controls the direction of the active cell once you enter data. i.e., when you hit the return key, to which cell does the curser go? Click the arrow if you want to change the direction.
    2. Enter the corresponding heights in C2 without commas. Label C2 "Height(ft)".
    3. Label third column (C3) as “Date”. Format the third columndate as "m/d/yy h:mm:ss" by choosing “Format Column” from the “Editor” pull down menu. Now type the dates each mountain was climbed into the third column. Example: Everest was first climbed in 5/29/53. Note that Minitab will add the hours/minutes/seconds as zeros as the default. The column name will change from C3 to C3-D once the dates are entered – the D stands for date format.
    4. Save the dataset to your Z drive using the “Save Current Worksheet” choice under the “File” pull down menu.

4. Sort the Data

We would like to sort the data by the height of the mountain.

    1. From the main menu, choose “Data” then “Sort”.
    2. Select all three columns: Mountains, Height(ft), and Date by holding down the control or shift key while clicking with the mouse. Then press: Select.
    3. In the “By column” space, type: “C2” and click on the Descending option.
    4. Store sorted data in new columns of your worksheet by typing column names C4, C5, C6 in without commas (only spaces) after clicking on the “Column(s) of current worksheet” choice.
    5. Press OK.

5. Label Columns

Label C4 "Mountains-s", C5 "Height(ft)-s", and C6 "Date-s". The extra s signifies that the data is sorted.

6. Rank the Data

    1. Label C7 : Rank.
    2. From the main menu, choose :”Calc” then “Patterned Data” then “Simple Set of Numbers”.
    3. Select the Rank variable for the “Store patterned data in” choice.
    4. From first value: 1.
    5. To last value: 14.
    6. In steps of: 1.
    7. Press OK.

7. Plotting the Heights in Feet

Make a scatterplot (“Graph”, “Scatterplot”, “Simple” menu choices) of the “Height(ft)-s" (Y variable) versus "Rank" (X variable). Type your name on the graph and print it.

8. Converting Heights from Feet to Meters

    1. Label C8 : Height(m).
    2. From the main menu, select “Calc” then “Calculator”.
    3. Store Result in variable : Height(m).
    4. To do the conversion, type in the expression box: C5*0.3048
    5. Press OK.

 9. Rounding to the Nearest Meter

    1. Label C9 "Height(m)-r"
    2. From the main menu, select “Calc” then “Calculator”
    3. Store result in: "Height(m)-r"
    4. Clear out anything leftover (from #8 above) in the Expression box and then choose Round from the list of functions.  Make sure the curser is in the Expression box.
    5. In "ROUND(number, num_digits) replace "number" with C8 and replace "num_digits" with 0 (zero) to round to the nearest whole number.

10. Plotting the Heights in Meters

Following the procedure from #7 to plot the heights in feet, now plot heights in meters. Print your graph.

11. Descriptive Statistics

Calculate the descriptive statistics for both "Height(ft)-s" and "Height(m)-r".

12. Comparison and Conclusion

Compare your graphs. How are they similar? How are they different? What conclusions can you make based on the shape of the graphs? Compare the means and standard deviations for each set of data. How are they related?

13. Turn In (Big Mountains Data)

    1. The Session window with Your Name at the top.
    2. The Worksheet Dataset
    3. Plot of Height(ft) vs. Rank
    4. Plot of Height(m) vs. Rank
    5. Comparison and Conclusion remarks (#12)

14. On your Own

Type in the Car Exhaust data from Section #16.  There were 46 cars measured for emissions in grams per mile of the following greenhouse gasses: Hydrocarbons (HC), Carbon Monoxide (CO) and Nitrous Oxide (NOX).

15. Turn In (Car Exhaust Data)

1.      Summary statistics (min, max, Q1, Q3, Range, Mean, Median, Mode and Standard Deviation) for each variable.

2.      A histogram and stemplot of the CO data.  Comment on the shape.

3.      A boxplot of the NOX data.  Any potential outliers?

4.      A Scatterplot of HC versus NOX.  Any pattern?

5.      A 3-D Scatterplot of all three variables. Any pattern?

16. Data Sets:         

 

 

Mountains

Mountain

Height (ft)

First Summit

Annapurna

26,545

June 3, 1950

Everest

29,028

May 29, 1953

Nanga Parbat

26,660

July 3, 1953

K2

28,250

July 31, 1954

Cho Oyu

26,906

October 19, 1954

Makalu

27,766

May 15, 1955

Kangchenjunga

28,169

May 25, 1955

Manaslu

26,781

May 9, 1956

Lhotse

27,940

May 18, 1956

Gasherbrum II

26,360

July 7, 1956

Broad Peak

26,400

June 9, 1957

Gasherbrum I

26,470

July 4, 1958

Dhaulagiri

26,795

May 13, 1960

Shisha Pangma

26,397

May 2, 1964

Car Exhaust

HC

CO

NOX

0.50

5.01

1.28

0.65

14.67

0.72

0.46

8.60

1.17

0.41

4.42

1.31

0.41

4.95

1.16

0.39

7.24

1.45

0.44

7.51

1.08

0.55

12.30

1.22

0.72

14.59

0.60

0.64

7.98

1.32

0.83

11.53

1.32

0.38

4.10

1.47

0.38

5.21

1.24

0.50

12.10

1.44

0.60

9.62

0.71

0.73

14.97

0.51

0.83

15.13

0.49

0.57

5.04

1.49

0.34

3.95

1.38

0.41

3.38

1.33

0.37

4.12

1.20

1.02

23.53

0.86

0.87

19.00

0.78

1.10

22.92

0.57

0.65

11.20

0.95

0.43

3.81

1.79

0.48

3.45

2.20

0.41

1.85

2.27

0.51

4.10

1.78

0.41

2.26

1.87

0.47

4.74

1.83

0.52

4.29

2.94

0.56

5.36

1.26

0.70

14.83

1.16

0.51

5.69

1.73

0.52

6.35

1.45

0.57

6.02

1.31

0.51

5.79

1.51

0.36

2.03

1.80

0.48

4.62

1.47

0.52

6.78

1.15

0.61

8.43

1.06

0.58

6.02

0.97

0.46

3.99

2.01

0.47

5.22

1.12

0.55

7.47

1.39