Identify a time dependent variable in your organization, business, or industry. Collect several measurements of this variable over time.
Draw a scatter diagram of this variable versus time. What are your observations?
Do you see any trend in the measurements? Explain. Do you see any seasonal variation in the measurements? Explain.
Add a trend line to your scatter diagram, and determine the trend equation. Interpret the trend equation.
Purpose: To demonstrate the application of time series analysis in your organization, business, or industry.
Example: I work for an electric utility company. Over the years the demand for electricity has been growing constantly. The electricity demand measured in Megawatts is an example of a time dependent variable. When I plot the scatter diagram of electricity demand versus time, I see both an upward trend and seasonal variation. The upward trend is the result of growing demand over time. The electricity demand is high during the summer season, and is low during winter season. This pattern is repeated year after year.
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I have a shop of ice-cream parlor. The sold of the ice-cream is more in the summer season as compared to other seasons.
The below data shows the sold of the ice-cream during different seasons from the year 2014 to 2018.
Time | Ice-cream sold('00') |
Winter-14 | 190 |
Spring-14 | 256 |
Summer-14 | 405 |
Monsoon-14 | 302 |
Winter-15 | 199 |
Spring-15 | 298 |
Summer-15 | 499 |
Monsoon-15 | 356 |
Winter-16 | 240 |
Spring-16 | 340 |
Summer-16 | 588 |
Monsoon-16 | 410 |
Winter-17 | 280 |
Spring-17 | 398 |
Summer-17 | 630 |
Monsoon-17 | 460 |
Winter-18 | 330 |
Spring-18 | 460 |
Summer-18 | 750 |
Monsoon-18 | 520 |
The above graph shows the seasonal effect in the sell of the ice-cream i.e. the sold is more during the summer and decreases gradually in another season then again in summer season the sold increases.
Also the sells increases due to the increase in the population.
The trend equation for this data is given by Y = 226.71 + 16.08X
Identify a time dependent variable in your organization, business, or industry. Collect several measurements of this...
LUCU ORICSS ULTIMIL E tion in the dependent variable that is explained by variation in the independent variable. (p. 246) sconnect Appendix 5A: Exercises EXERCISE 5A-1 High-Low Method L05-10 The Cheyenne Hotel in Big Sky, Montana, has accumulated records of the total electrical costs of the hotel and the number of occupancy-days over the last year. An occupancy-day represents a room rented for one day. The hotel's business is highly seasonal, with peaks occurring during the ski season and in...
The dependent variable is the position (y-axis) and the independent variable is the time (x-axis). This is the measured position of a rock as it falls from the top of a very high cliff and obeys the equations y = 1/2gt2. Make sure you label the plot properly. Right click on a data point in the graph and add a “Trend line.” Select a polynomial of order 2. This is a parabolic equation and describes an object falling under constant...
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This is a small business started by Alex Lopez in 1980. He was 22 years old, and had just graduated from UTSA with a degree in Business. As a young entrepreneur, he bought a greenhouse, and started a hydroponic farm growing tomatoes. Growing various vegetables in water was a new industry at that time. Alex's business is operating in a perfectly competitive industry, competing with other greenhouse and field producers in...
Assume for a moment that these 20 houses made up the entire population of houses in San Antonio. Use the Data Analysis Sampling function to choose a random sample of 7 house prices from the population. Put a label called "Sample of 7" over the list you create. 4. 3. Highlight all the data, including both Square Footage and Price, and use the Insert Scatter function to create a Scatter Diagram. Change the title and add a linear trend line...
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6. Confidence and prediction Interval estimates Aa Aa You are a starting pitcher in the major leagues. It's January 2008, and you are in the process of negotiating your salary for the 2008 season. You hire a statisticlan to help you with your negotiations. She specifies the folowing simple linear regression model: where y2008 salary (in millions of dollars), and x performance during the regular 2007 season Then she selects a random sample of 50 major...
Since early Roman days, people have used greenhouses to grow plants—particularly to enjoy fruits and vegetables out of season. But not until the 1990s did greenhouses begin to gain popularity in the United States. The timing couldn’t be better. The amount of farmable land per capita in the world continues to shrink, and over the next 50 years, world population is expected to increase by 3 billion. At the same time, economists estimate the demand for farm products will double....
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Problem 4: Variables that may affect Grades The data set contains a random sample of STAT 250 Final Exam Scores out of 80 points. For each individual sampled, the time (in hours per week) that the student spent participating in a GMU club or sport and working for pay outside of GMU was recorded. Values of 0 indicate the students either does not participate in a club or sport or does not work a job for pay. The goal of...
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A B С D E F G H 1 WinterRain HarvestRain 160 Age 31 2 600 3 690 80 4. 502 130 Year 1952 1953 1955 1957 1958 1959 1960 5 420 110 187 30 28 26 25 24 23 6 7 582 485 763 830 8 9 1961 22 10 1962 697 21 20 11 12 1963 1964...
Please help me complete this.
I have been struggling for quite some time, and mainly I need
the answer.
Thank you!
A B С D E F G H 1 WinterRain HarvestRain 160 Age 31 2 600 3 690 80 4. 502 130 Year 1952 1953 1955 1957 1958 1959 1960 5 420 110 187 30 28 26 25 24 23 6 7 582 485 763 830 8 9 1961 22 10 1962 697 21 20 11 12 1963 1964...