On San Martin Boulevard, embedded sensors kept track of the vehicle traffic count each hour for five weekdays, Monday through Friday, between 6 a.m. and 8 p.m. (5 weeks x 14 hours = 70 observations). 2000 2500 3000 3500 4000 4500 5000 Vehicles per Hour (a) Visually estimate the quartiles Q1, Q2, Q3. Q1 = Q2 = Q3 = (b) Estimate Xmin and xmax• Xmin = Xmax = %3D
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
On San Martin Boulevard, embedded sensors kept track of the vehicle traffic count each hour for five weekdays, Monday through Friday, between 6 a.m. and 8 p.m. (5 weeks × 14 hours = 70 observations).
(a) Visually estimate the
| Q1 = | ||
| Q2 = | ||
| Q3 = | ||
(b) Estimate xmin and xmax.
| xmin = | ||
| xmax = | ||
![**Traffic Analysis on San Martin Boulevard**
On San Martin Boulevard, embedded sensors monitored vehicle traffic counts each hour on weekdays, Monday through Friday, from 6 a.m. to 8 p.m. The data was collected over five weeks, resulting in 70 observations (5 weeks × 14 hours = 70 observations).
**Box Plot Description:**
The provided box plot illustrates the distribution of vehicle counts per hour. Here's how to interpret the diagram:
- **Box Plot Components:**
- The box represents the interquartile range (IQR), which spans from the first quartile (Q1) to the third quartile (Q3).
- The line inside the box indicates the median (Q2).
- The "whiskers" extend from the quartiles to the smallest and largest observations that are not outliers.
- **Axes:**
- The x-axis is labeled "Vehicles per Hour," with values ranging from 2000 to 5000.
**Tasks:**
(a) **Visually Estimate the Quartiles \(Q_1, Q_2, Q_3\):**
- \(Q_1 = \) [Enter your estimate]
- \(Q_2 = \) [Enter your estimate]
- \(Q_3 = \) [Enter your estimate]
(b) **Estimate \(x_{min}\) and \(x_{max}\):**
- \(x_{min} = \) [Enter your estimate]
- \(x_{max} = \) [Enter your estimate]
Use the box plot to provide estimates for the quartiles and range values. These estimates help understand traffic flow patterns and variations throughout the observed period.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fdf9350e0-c4ce-45b2-8bf6-798a5b7f5cee%2F4fe4a782-28b7-4a96-a247-253fa62f631e%2Fl4p2d5_processed.png&w=3840&q=75)
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