1. How many outliers does the online set of sales transactions include? 2. How many outliers does the in-person set of sales transactions include? 3. Is the average (mean) sales transaction amount higher for online sales or in-person sales? 4. Which of the following statements accurately describes the skew of the two datasets? 5. What is the lowest value of the entire dataset (taking into account both in-person and online sales?) (Round to 2 decimal places.) The average is higher for online sales. Both datasets are skewed positively. $ 142 X 51 X 2.52 338
1. How many outliers does the online set of sales transactions include? 2. How many outliers does the in-person set of sales transactions include? 3. Is the average (mean) sales transaction amount higher for online sales or in-person sales? 4. Which of the following statements accurately describes the skew of the two datasets? 5. What is the lowest value of the entire dataset (taking into account both in-person and online sales?) (Round to 2 decimal places.) The average is higher for online sales. Both datasets are skewed positively. $ 142 X 51 X 2.52 338
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Use the excel sheet/graph to find how many outliers there are online!
Transcribed Image Text:**Statistical Data Analysis**
The table summarizes statistical data for two categories: "Online" and "In-Person."
### Online
- **Mean**: 40.55
- **Standard Error**: 2.58
- **Median**: 33.90
- **Mode**: 7.52
- **Standard Deviation**: 30.74
- **Sample Variance**: 944.94
- **Kurtosis**: -0.018
- **Skewness**: 0.85
- **Range**: 137.5
- **Minimum**: 2.52
- **Maximum**: 140.02
- **Sum**: 5758.59
- **Count**: 142
### In-Person
- **Mean**: 33.64
- **Standard Error**: 3.46
- **Median**: 26.97
- **Mode**: 12.52
- **Standard Deviation**: 24.71
- **Sample Variance**: 610.81
- **Kurtosis**: -0.41
- **Skewness**: 0.78
- **Range**: 95.55
- **Minimum**: 2.87
- **Maximum**: 98.42
- **Sum**: 1715.72
- **Count**: 51
### Box Plot (on the right side of the image)
The box plot visualizes the distribution for the "Online" and "In-Person" data:
- **Boxes** represent the interquartile range (IQR) where 50% of the data points lie.
- The left box (blue) corresponds to "Online" data.
- The right box (orange) corresponds to "In-Person" data.
- **Whiskers** extend to show the range from the minimum to maximum values, excluding outliers.
- **Data Points** outside the whiskers represent outliers, indicating values significantly different from other data points.
- **Medians** are marked within each box, showing the middle value of the dataset.
This analysis helps in understanding the distribution differences between online and in-person categories.
Transcribed Image Text:**Sales Transactions Data Analysis**
The table below provides answers to several key questions regarding sales transactions, both online and in-person.
| Question | Answer |
|----------|--------|
| 1. How many outliers does the online set of sales transactions include? | 142 ❌ |
| 2. How many outliers does the in-person set of sales transactions include? | 51 ❌ |
| 3. Is the average (mean) sales transaction amount higher for online sales or in-person sales? | The average is higher for online sales. ✅ |
| 4. Which of the following statements accurately describes the skew of the two datasets? | Both datasets are skewed positively. ✅ |
| 5. What is the lowest value of the entire dataset (taking into account both in-person and online sales)? (Round to 2 decimal places.) | $2.52 ✅ |
**Explanation of Table**
- **Questions 1 and 2:** Indicate the number of outliers in online and in-person sales, though incorrect answers are marked.
- **Question 3:** States that average sales transactions are higher online.
- **Question 4:** Confirms both datasets are positively skewed.
- **Question 5:** Provides the lowest transaction value across datasets, rounded to two decimal places.
This information can be used to better understand disparities in sales data, guiding decisions on sales strategies.
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