Answer:
b
Step-by-step explanation:
There appears to be a positive correlation between the number of hour spent studydng and the score on the test.
When identifying the independent and dependent quantities, we think about what would cause the other to change. The score on the test would not cause the number of hours spent studying to change; rather, the number of hours spent studying would cause the score to change. This means that the number of hours studying would be the independent quantity and the score would be the dependent quantity.
Plotting the graph with the time studying on the x-axis (independent) and the score on the y-axis (dependent) gives you the graph shown. You can see in the image that there seems to be a positive correlation; the data seem to generally be heading upward.
Answer:
a)
Mean = sum of all numbers in dataset / total number in dataset
Mean = 8130/15 = 542
Median:
The median is also the number that is halfway into the set.
For median, we need to sort the data and then find the middle number which in our case is 546. Below is the sorted data
486 516 523 523 529 534 538 546 548 551 552 558 566 574 586
Standard Deviation (SD). Here X represents dataset and N= count of numbers in data
As per the SD formula, which is Sqrt ( sum (X_i - Meanx(X))/(N-1))
SD= 25.082
2) Formula for coefficient of skewness using Pearson's method (using median) is,
SK = 3* ( Mean (X) - Median(X))/(Standard Deviation) = 3*(542-546)/25.082 = -0.325
3) coefficient of skewness using the software method is also same which is -0.325
Answer:
k = 2
Step-by-step explanation:
subtract 9 from both sides and you have 3k=6
then divide by three on both sides to get 2