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On January 28, 1986 the space shuttle Challenger exploded. Seven astronauts died because two large rubber O-rings leaked during takeoff. These rings had lost their resiliency because of the low temperature at the time of the flight. The air temperature was about 00 Celsius, and the temperature of the O-rings about 6 degrees below that. The link between O-ring damage and ambient temperature had been established prior to the flight. The engineers at Morton Thiokol, Inc had recommended that the flight be delayed. Unfortunately their argument wasn’t persuasive enough, and the launch proceeded with disastrous consequences. The engineers had failed to display the link between ambient temperature and O-ring damage in a clear and unambiguous fashion. All that was needed was a simple scatterplot. The data is given below. Temperature (0 C) - Column 1 Damage Index - Column 2 12 11 14 4 14 4 17 2 19 0 19 0 19 0 19 0 19 0 20 0 21 4 21 0 21 4 21 0 21 0 22 0 23 0 24 4 24 0 24 0 26 0 26 0 27 0 Construct a scatterplot from the data. Then answer the following: (a) Interpret the scatterplot (comment on association, form, strength, and outliers). (b) Based on this graphic, what recommendation would you have made for a flight if the forecast was for below 00 Celsius?
@Abhisar @Clalgee @ParthKohli
@texaschic101 @Nnesha @Conqueror
have you entered the data into the software?
No I need help with the whole question! I have NO idea what to do. Can you please help? @BPDlkeme234
I will enter the data, just give me a minute
Okay thank you @BPDlkeme234
Now, all I did to create that was copy and paste the data values you gave me into: http://www.alcula.com/calculators/statistics/scatter-plot/
(a) Interpret the scatterplot (comment on association, form, strength, and outliers). There is a serious outlier at (x,y) = (12,11)
in terms of association, which I take to mean correlation, there are parts of the data which are strongly correlated, and part of the data that are not strongly correlated (that may also imply strength).
At 0 degrees, the data is strongly correlated, however for values other than zero degrees the results are weakly correlated.
Form: what can you say about that? we will consider this as distribution of data values, the values at zero degrees show a linear pattern, however values above this show an irregular form.
Umm is it more skewed to the right? @BPDlkeme234
I considered skew in my answer, but, skew only applies where the frequency distribution is a regular shape which this is not
Okay but what about b? @BPDlkeme234
I have no idea what its asking..
Okay, part b
what is it asking? @BPDlkeme234
(b) Based on this graphic, what recommendation would you have made for a flight if the forecast was for below 00 Celsius? According to the diagram, column 1(the x-axis) equals temp in degrees celsius which goes from 12 to 26 degrees,the damage index (the y-axis) goes from 0 to 11. Based on that: 1. At 12 degrees, the damage index was 11 2.At 14 degrees the damage index was 4 (a big drop for a two degree increase in temperature) 3.At 16 degrees, the damge index drops to 2 Now there are totally weird results for 21 degrees and 24, i.e. it records that there are two different values
However, you are asked what recommendation you would give if it drops below 0 degrees celsius, and based on the fact that, at 16 degrees the damage index is 2, and at 14 degrees, this rises to 4 and at 12 degrees this rises again to 11, I would have to say that at zero the damage would be catastrophic
P.S. Richard Feynman, who demonstrated the problems with the O-rings, is one of my favourite scientists