, Principles of Data Science
Chapter 3
Descriptive Statistics: Statistical Measurements and Probability Distributions
Quantitative Problems
[3.1, LO 3.1.1]
1.
Dataset A Description Data
Number of cars entering Sample of 10 counts:
a 15, 18, 4, 15, 8,
parking garage in a 11, 13, 7, 16, 24
1-hour time period
a. For Dataset A, calculate the mean and a 10% trimmed mean (round answers to 1
decimal place). Use technology as appropriate.
b. Is there any benefit in using the trimmed mean versus the mean for this dataset?
Solution a: Mean=16.4 , 10 % Trimmed mean=12.9
To find the mean, add up the data values and divide by the number of data values, which is 10.
The sum of the data values is 164 and dividing this by 10 results in a mean of 16.4. To find the
10% trimmed mean, delete 10% of the data values from the lower end and from the upper end
of the ordered dataset. Since there are 10 data values in the dataset, 10% of 10 is 1, so proceed
to delete one data value from the lower end of the sorted data and delete one data value from
the upper end of the sorted data. In this example, delete the smallest data value and delete the
largest data value and then find the mean for the remaining 8 data values, which is 12.875
(round to 12.9).
To find the mean using Excel, copy the data into cells A1 to A10, and in any empty cell type in
the Excel command:
¿ AVERAGE( A 1 : A 10)
To find the mean using Python Pandas, first create a csv file with all the data items in the
dataset. Suppose the .csv file is named as cars.csv, uploaded to the Google Drive properly, and
loaded by *gdown* properly. The following Python code returns multiple summary statistics of
the dataset, and the “mean” value indicates the average.
Python code:
import pandas as pd
data = pd.read_csv(“cars.csv”)
11/11/24 For more free, peer-reviewed, openly licensed resources visit OpenStax.org. 2
Chapter 3
Descriptive Statistics: Statistical Measurements and Probability Distributions
Quantitative Problems
[3.1, LO 3.1.1]
1.
Dataset A Description Data
Number of cars entering Sample of 10 counts:
a 15, 18, 4, 15, 8,
parking garage in a 11, 13, 7, 16, 24
1-hour time period
a. For Dataset A, calculate the mean and a 10% trimmed mean (round answers to 1
decimal place). Use technology as appropriate.
b. Is there any benefit in using the trimmed mean versus the mean for this dataset?
Solution a: Mean=16.4 , 10 % Trimmed mean=12.9
To find the mean, add up the data values and divide by the number of data values, which is 10.
The sum of the data values is 164 and dividing this by 10 results in a mean of 16.4. To find the
10% trimmed mean, delete 10% of the data values from the lower end and from the upper end
of the ordered dataset. Since there are 10 data values in the dataset, 10% of 10 is 1, so proceed
to delete one data value from the lower end of the sorted data and delete one data value from
the upper end of the sorted data. In this example, delete the smallest data value and delete the
largest data value and then find the mean for the remaining 8 data values, which is 12.875
(round to 12.9).
To find the mean using Excel, copy the data into cells A1 to A10, and in any empty cell type in
the Excel command:
¿ AVERAGE( A 1 : A 10)
To find the mean using Python Pandas, first create a csv file with all the data items in the
dataset. Suppose the .csv file is named as cars.csv, uploaded to the Google Drive properly, and
loaded by *gdown* properly. The following Python code returns multiple summary statistics of
the dataset, and the “mean” value indicates the average.
Python code:
import pandas as pd
data = pd.read_csv(“cars.csv”)
11/11/24 For more free, peer-reviewed, openly licensed resources visit OpenStax.org. 2
