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Are the distributions all normal or is at least
one skewed?
Normal? Skewed?
The Normal Distribution is a distribution that has most
of the data in the center with decreasing amounts
evenly distributed to the left and the right.
Skewed Distribution is distribution with data clumped
up on one side or the other with decreasing amounts
trailing off to the left or the right.
Central Tendency, Spread, or Symmetry?
The Normal Distribution is a distribution that has most
of the data in the center with decreasing amounts
evenly distributed to the left and the right.
The Skewed Distribution is distribution with data
clumped up on one side or the other with decreasing
amounts trailing off to the left or the right.
Central Tendency, Spread, or Symmetry?
Right skewed Left skewed
Why is this important to know?
Why is this important to know?
Because the means and standard deviations of
samples with skewed distributions do not
generalize to the population well.
This is because the skewed distributions means
are pulled toward the tail of the distribution.
Why is this important to know?
Because the means and standard deviations of
samples with skewed distributions do not
generalize to the population well.
This is because the skewed distributions means
are pulled toward the tail of the distribution.
The Population
Skewed
Sample
Why is this important to know?
Because the means and standard deviations of
samples with skewed distributions do not
generalize to the population well.
This is because the skewed distributions means
are pulled toward the tail of the distribution.
The Population
Skewed
Sample
Why is this important to know?
Because the means and standard deviations of
samples with skewed distributions do not
generalize to the population well.
This is because the skewed distributions means
are pulled toward the tail of the distribution.
The Population
Skewed
Sample
Why is this important to know?
Because the means and standard deviations of
samples with skewed distributions do not
generalize to the population well.
This is because the skewed distributions means
are pulled toward the tail of the distribution.
The Population
Skewed
Sample
mean mean
How can you tell if a distribution is
• Normal?
How can you tell if a distribution is
• Normal?
or
• Skewed?
We will show you the answer to that question
within the context of a problem.
Problem
Is there a significant difference between drivers of
old cars and drivers of new cars in terms of average
freeway driving speed?
First let’s determine if the old and new car
distributions are normal or skewed.
Problem
Is there a significant difference between drivers of
old cars and drivers of new cars in terms of average
freeway driving speed?
First let’s determine if the old and new car
distributions are normal or skewed.
Data Set
Access the data set below:
Link to data set
SPSS
Copy and paste the data into SPSS by following
the instructions at this link.
Note – go to the 2nd page of the instructions
How to check for skew in SPSS
Select Analyze
Step 1
Descriptive – Compare Means - Means
Step 2
Select the Dependent Variable – click the arrow
Step 3
Select the Dependent Variable – click the arrow
Step 3
Select the Independent Variable – click the arrow
Step 3
Click Options
Step 4
Bring Skew and Standard Error of the Skew over
Step 5
Click OK
Step 5
Output
Let’s Interpret!
Let’s Interpret!
First, we have to determine if this is a descriptive
or inferential question.
Let’s Interpret!
If descriptive, we look just at this value
Let’s Interpret!
For the new car distribution the skewness is -.953.
Let’s Interpret!
For the new car distribution the skewness is -.953.
If the skewness is below -2.0 or above +2.0 then
the distribution is considered skewed.
Let’s Interpret!
For the new car distribution the skewness is -.953.
Because -.953 is between -2.0 and +2.0 then the
distribution is considered Normal
Let’s Interpret!
Therefore the new car distribution is considered
Normal if we are dealing with descriptive statistics
But …
We are NOT dealing with descriptive statistics.
We are dealing with inferential statistics.
Therefore, we must take a different approach.
Everyone in
the population
We are NOT dealing with descriptive statistics.
We are dealing with inferential statistics.
Therefore, we must take a different approach.
Everyone in
the population
Everyone in
the population
Sample
We are NOT dealing with descriptive statistics.
We are dealing with inferential statistics.
Therefore, we must take a different approach.
Everyone in
the population
Everyone in
the population
Sample
We must . . .
. . divide the skewness by the standard error of
skewness.
We must . . .
. . divide the skewness by the standard error of
skewness.
We must . . .
. . divide the skewness by the standard error of
skewness.
We must . . .
. . divide the skewness by the standard error of
skewness.
We must . . .
. . divide the skewness by the standard error of
skewness.
We must . . .
. . divide the skewness by the standard error of
skewness.
We must . . .
. . divide the skewness by the standard error of
skewness.
-1.69
We must . . .
The reason we do this will be explained later on in
the course.
-1.69
Let’s Interpret!
-1.69
Let’s Interpret!
For the new car distribution the skewness is -1.69.
-1.69
Let’s Interpret!
For the new car distribution the skewness is -1.69.
-1.69
If the skewness is below -2.0 or above +2.0 then
the distribution is considered skewed.
Let’s Interpret!
Because -1.69 is between -2.0 and +2.0 then the
distribution is considered Normal
For the new car distribution the skewness is -1.69.
-1.69
Let’s Interpret!
-1.69
Therefore the new car distribution is considered
Normal if we are dealing with inferential statistics
Now the focus turns to the skewness
of the old car distribution.
Calculating Skew
. . divide the skewness by the standard error of
skewness.
Calculating Skew
. . divide the skewness by the standard error of
skewness.
-4.26
-4.26
Let’s Interpret!
Let’s Interpret!
-4.26
For the old car distribution the skewness is -4.26.
Let’s Interpret!
If the skewness is below -2.0 or above +2.0 then
the distribution is considered skewed.
-4.26
For the old car distribution the skewness is -4.26.
Let’s Interpret!
Because -4.26 is less than -2.0 then the
distribution is considered negatively skewed
-4.26
For the old car distribution the skewness is -4.26.
Let’s Interpret!
If the skewness had been positive +4.26 it would
have been positively or right skewed:
For the old car distribution the skewness is -4.26.
Let’s Interpret!
But in this case, the old car distribution is considered
negative or left skewed if we are dealing with
inferential statistics
-4.26
Let’s practice
Old car / new car skew problem with
different data set.
Is the old car data set skewed or
normal (inferential study)?
Is the old car data set skewed or
normal?
Report
speed
new_old_car Mean N Std. Deviation Skewness
Std. Error of
Skewness
New car 72.81 16 6.595 -.953 .564
Old car 79.94 17 18.081 3.344 .550
Total 76.48 33 14.034 -1.832 .409
Normal? Skewed?
Report
speed
new_old_car Mean N Std. Deviation Skewness
Std. Error of
Skewness
New car 72.81 16 6.595 -.953 .564
Old car 79.94 17 18.081 3.344 .550
Total 76.48 33 14.034 -1.832 .409
Is the old car data set skewed or
normal?
+6.06
Normal? Skewed?
Report
speed
new_old_car Mean N Std. Deviation Skewness
Std. Error of
Skewness
New car 72.81 16 6.595 -.953 .564
Old car 79.94 17 18.081 3.344 .550
Total 76.48 33 14.034 -1.832 .409
Is the old car data set skewed or
normal?
+6.06
Normal? Skewed?
Report
speed
new_old_car Mean N Std. Deviation Skewness
Std. Error of
Skewness
New car 72.81 16 6.595 -.953 .564
Old car 79.94 17 18.081 3.344 .550
Total 76.48 33 14.034 -1.832 .409
Is the old car data set skewed or
normal?
+6.06
Normal? Skewed?
If the skewness is below -2.0 or above +2.0 then
the distribution is considered skewed.
Report
speed
new_old_car Mean N Std. Deviation Skewness
Std. Error of
Skewness
New car 72.81 16 6.595 -.953 .564
Old car 79.94 17 18.081 3.344 .550
Total 76.48 33 14.034 -1.832 .409
Is the old car data set skewed or
normal?
+6.06
Normal? Skewed?
Because +6.06 is greater than +2.0 then the
distribution is considered positively or right skewed.
Is the new car data set skewed or
normal?
Normal? Skewed?
Is the new car data set skewed or
normal?
Normal? Skewed?
Report
speed
new_old_car Mean N Std. Deviation Skewness
Std. Error of
Skewness
New car 72.81 16 6.595 1.813 .993
Old car 79.94 17 18.081 -2.344 .550
Total 76.48 33 14.034 -1.832 .409
Report
speed
new_old_car Mean N Std. Deviation Skewness
Std. Error of
Skewness
New car 72.81 16 6.595 1.813 .993
Old car 79.94 17 18.081 -2.344 .550
Total 76.48 33 14.034 -1.832 .409
Is the new car data set skewed or
normal?
Normal? Skewed?
1.83
Report
speed
new_old_car Mean N Std. Deviation Skewness
Std. Error of
Skewness
New car 72.81 16 6.595 1.813 .993
Old car 79.94 17 18.081 -2.344 .550
Total 76.48 33 14.034 -1.832 .409
Is the new car data set skewed or
normal?
Normal? Skewed?
1.83
Report
speed
new_old_car Mean N Std. Deviation Skewness
Std. Error of
Skewness
New car 72.81 16 6.595 1.813 .993
Old car 79.94 17 18.081 -2.344 .550
Total 76.48 33 14.034 -1.832 .409
Is the new car data set skewed or
normal?
Normal? Skewed?
1.83
If the skewness is between -2.0 and +2.0 then the
distribution is considered normal.
Report
speed
new_old_car Mean N Std. Deviation Skewness
Std. Error of
Skewness
New car 72.81 16 6.595 1.813 .993
Old car 79.94 17 18.081 -2.344 .550
Total 76.48 33 14.034 -1.832 .409
Is the new car data set skewed or
normal?
Normal? Skewed?
1.83
Because 1.83 is between -2.0 and +2.0 then the
distribution is considered normal.
After calculating the skew for the data set in your
original problem, determine if the distributions are
all normal or is there at least one that is skewed?
Normal? Skewed?

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Normal or skewed distributions (inferential)

  • 1. Are the distributions all normal or is at least one skewed? Normal? Skewed?
  • 2. The Normal Distribution is a distribution that has most of the data in the center with decreasing amounts evenly distributed to the left and the right. Skewed Distribution is distribution with data clumped up on one side or the other with decreasing amounts trailing off to the left or the right. Central Tendency, Spread, or Symmetry?
  • 3. The Normal Distribution is a distribution that has most of the data in the center with decreasing amounts evenly distributed to the left and the right. The Skewed Distribution is distribution with data clumped up on one side or the other with decreasing amounts trailing off to the left or the right. Central Tendency, Spread, or Symmetry? Right skewed Left skewed
  • 4. Why is this important to know?
  • 5. Why is this important to know? Because the means and standard deviations of samples with skewed distributions do not generalize to the population well. This is because the skewed distributions means are pulled toward the tail of the distribution.
  • 6. Why is this important to know? Because the means and standard deviations of samples with skewed distributions do not generalize to the population well. This is because the skewed distributions means are pulled toward the tail of the distribution. The Population Skewed Sample
  • 7. Why is this important to know? Because the means and standard deviations of samples with skewed distributions do not generalize to the population well. This is because the skewed distributions means are pulled toward the tail of the distribution. The Population Skewed Sample
  • 8. Why is this important to know? Because the means and standard deviations of samples with skewed distributions do not generalize to the population well. This is because the skewed distributions means are pulled toward the tail of the distribution. The Population Skewed Sample
  • 9. Why is this important to know? Because the means and standard deviations of samples with skewed distributions do not generalize to the population well. This is because the skewed distributions means are pulled toward the tail of the distribution. The Population Skewed Sample mean mean
  • 10. How can you tell if a distribution is • Normal?
  • 11. How can you tell if a distribution is • Normal? or • Skewed?
  • 12. We will show you the answer to that question within the context of a problem.
  • 13. Problem Is there a significant difference between drivers of old cars and drivers of new cars in terms of average freeway driving speed? First let’s determine if the old and new car distributions are normal or skewed.
  • 14. Problem Is there a significant difference between drivers of old cars and drivers of new cars in terms of average freeway driving speed? First let’s determine if the old and new car distributions are normal or skewed.
  • 15. Data Set Access the data set below: Link to data set
  • 16. SPSS Copy and paste the data into SPSS by following the instructions at this link. Note – go to the 2nd page of the instructions
  • 17. How to check for skew in SPSS
  • 19. Descriptive – Compare Means - Means Step 2
  • 20. Select the Dependent Variable – click the arrow Step 3
  • 21. Select the Dependent Variable – click the arrow Step 3
  • 22. Select the Independent Variable – click the arrow Step 3
  • 24. Bring Skew and Standard Error of the Skew over Step 5
  • 28. Let’s Interpret! First, we have to determine if this is a descriptive or inferential question.
  • 29. Let’s Interpret! If descriptive, we look just at this value
  • 30. Let’s Interpret! For the new car distribution the skewness is -.953.
  • 31. Let’s Interpret! For the new car distribution the skewness is -.953. If the skewness is below -2.0 or above +2.0 then the distribution is considered skewed.
  • 32. Let’s Interpret! For the new car distribution the skewness is -.953. Because -.953 is between -2.0 and +2.0 then the distribution is considered Normal
  • 33. Let’s Interpret! Therefore the new car distribution is considered Normal if we are dealing with descriptive statistics
  • 35. We are NOT dealing with descriptive statistics. We are dealing with inferential statistics. Therefore, we must take a different approach. Everyone in the population
  • 36. We are NOT dealing with descriptive statistics. We are dealing with inferential statistics. Therefore, we must take a different approach. Everyone in the population Everyone in the population Sample
  • 37. We are NOT dealing with descriptive statistics. We are dealing with inferential statistics. Therefore, we must take a different approach. Everyone in the population Everyone in the population Sample
  • 38. We must . . . . . divide the skewness by the standard error of skewness.
  • 39. We must . . . . . divide the skewness by the standard error of skewness.
  • 40. We must . . . . . divide the skewness by the standard error of skewness.
  • 41. We must . . . . . divide the skewness by the standard error of skewness.
  • 42. We must . . . . . divide the skewness by the standard error of skewness.
  • 43. We must . . . . . divide the skewness by the standard error of skewness.
  • 44. We must . . . . . divide the skewness by the standard error of skewness. -1.69
  • 45. We must . . . The reason we do this will be explained later on in the course. -1.69
  • 47. Let’s Interpret! For the new car distribution the skewness is -1.69. -1.69
  • 48. Let’s Interpret! For the new car distribution the skewness is -1.69. -1.69 If the skewness is below -2.0 or above +2.0 then the distribution is considered skewed.
  • 49. Let’s Interpret! Because -1.69 is between -2.0 and +2.0 then the distribution is considered Normal For the new car distribution the skewness is -1.69. -1.69
  • 50. Let’s Interpret! -1.69 Therefore the new car distribution is considered Normal if we are dealing with inferential statistics
  • 51. Now the focus turns to the skewness of the old car distribution.
  • 52. Calculating Skew . . divide the skewness by the standard error of skewness.
  • 53. Calculating Skew . . divide the skewness by the standard error of skewness. -4.26
  • 55. Let’s Interpret! -4.26 For the old car distribution the skewness is -4.26.
  • 56. Let’s Interpret! If the skewness is below -2.0 or above +2.0 then the distribution is considered skewed. -4.26 For the old car distribution the skewness is -4.26.
  • 57. Let’s Interpret! Because -4.26 is less than -2.0 then the distribution is considered negatively skewed -4.26 For the old car distribution the skewness is -4.26.
  • 58. Let’s Interpret! If the skewness had been positive +4.26 it would have been positively or right skewed: For the old car distribution the skewness is -4.26.
  • 59. Let’s Interpret! But in this case, the old car distribution is considered negative or left skewed if we are dealing with inferential statistics -4.26
  • 61. Old car / new car skew problem with different data set.
  • 62. Is the old car data set skewed or normal (inferential study)?
  • 63. Is the old car data set skewed or normal? Report speed new_old_car Mean N Std. Deviation Skewness Std. Error of Skewness New car 72.81 16 6.595 -.953 .564 Old car 79.94 17 18.081 3.344 .550 Total 76.48 33 14.034 -1.832 .409 Normal? Skewed?
  • 64. Report speed new_old_car Mean N Std. Deviation Skewness Std. Error of Skewness New car 72.81 16 6.595 -.953 .564 Old car 79.94 17 18.081 3.344 .550 Total 76.48 33 14.034 -1.832 .409 Is the old car data set skewed or normal? +6.06 Normal? Skewed?
  • 65. Report speed new_old_car Mean N Std. Deviation Skewness Std. Error of Skewness New car 72.81 16 6.595 -.953 .564 Old car 79.94 17 18.081 3.344 .550 Total 76.48 33 14.034 -1.832 .409 Is the old car data set skewed or normal? +6.06 Normal? Skewed?
  • 66. Report speed new_old_car Mean N Std. Deviation Skewness Std. Error of Skewness New car 72.81 16 6.595 -.953 .564 Old car 79.94 17 18.081 3.344 .550 Total 76.48 33 14.034 -1.832 .409 Is the old car data set skewed or normal? +6.06 Normal? Skewed? If the skewness is below -2.0 or above +2.0 then the distribution is considered skewed.
  • 67. Report speed new_old_car Mean N Std. Deviation Skewness Std. Error of Skewness New car 72.81 16 6.595 -.953 .564 Old car 79.94 17 18.081 3.344 .550 Total 76.48 33 14.034 -1.832 .409 Is the old car data set skewed or normal? +6.06 Normal? Skewed? Because +6.06 is greater than +2.0 then the distribution is considered positively or right skewed.
  • 68. Is the new car data set skewed or normal? Normal? Skewed?
  • 69. Is the new car data set skewed or normal? Normal? Skewed? Report speed new_old_car Mean N Std. Deviation Skewness Std. Error of Skewness New car 72.81 16 6.595 1.813 .993 Old car 79.94 17 18.081 -2.344 .550 Total 76.48 33 14.034 -1.832 .409
  • 70. Report speed new_old_car Mean N Std. Deviation Skewness Std. Error of Skewness New car 72.81 16 6.595 1.813 .993 Old car 79.94 17 18.081 -2.344 .550 Total 76.48 33 14.034 -1.832 .409 Is the new car data set skewed or normal? Normal? Skewed? 1.83
  • 71. Report speed new_old_car Mean N Std. Deviation Skewness Std. Error of Skewness New car 72.81 16 6.595 1.813 .993 Old car 79.94 17 18.081 -2.344 .550 Total 76.48 33 14.034 -1.832 .409 Is the new car data set skewed or normal? Normal? Skewed? 1.83
  • 72. Report speed new_old_car Mean N Std. Deviation Skewness Std. Error of Skewness New car 72.81 16 6.595 1.813 .993 Old car 79.94 17 18.081 -2.344 .550 Total 76.48 33 14.034 -1.832 .409 Is the new car data set skewed or normal? Normal? Skewed? 1.83 If the skewness is between -2.0 and +2.0 then the distribution is considered normal.
  • 73. Report speed new_old_car Mean N Std. Deviation Skewness Std. Error of Skewness New car 72.81 16 6.595 1.813 .993 Old car 79.94 17 18.081 -2.344 .550 Total 76.48 33 14.034 -1.832 .409 Is the new car data set skewed or normal? Normal? Skewed? 1.83 Because 1.83 is between -2.0 and +2.0 then the distribution is considered normal.
  • 74. After calculating the skew for the data set in your original problem, determine if the distributions are all normal or is there at least one that is skewed? Normal? Skewed?