Economy excel project

Excel Practice I

Cindy Smith

ECON 261-1001

Professor Assané

Fall 2018

Acknowledgements:

To my family…

For tolerating all the time I spend studying while finishing my degree;

And for supporting the time and effort that goes into higher education while encouraging me to do my best.

Distance of Fire Stations and Fire Damage

Introduction

Residential fires can cause varying amounts of damage, resulting in devastating loss in some cases. Of the many variables to consider when determining the ability to extinguish the fire, one factor is the distance of the fire station in relation to the location of the burning residence. A fire insurance company collected data to show the relationship between fire station locations and the amount of damage caused by a fire. A hypothesis was drawn to answer the question of how relevant the distance between a fire station and a fire are in correlation to reduce the amount of damages sustained. Data from recent fires were used to create the following tables depicting the mean, standard deviation, and the minimum and maximum variables used to test and validate the hypothesis.

Descriptive Statistics

Table 1: Descriptive Statistics for Fire Damages

The table shows a sample data set from fifteen fires, with the mean (average) distance of a fire station from a fire being 3.27 miles, with a standard deviation of 1.57 miles. The amount of damages in dollars (thousands) in relation to the mean was $26.41, and $8.07 in relation to the standard deviation. At a minimum distance of 0.7 miles, the damages totaled $14.1 thousand dollars. The maximum distance was 6.1 miles, with the damages totaling $43.2 thousand dollars. The statistics show a relationship between the distance of fire stations and the amount of damages incurred.

Correlation Coefficient

Table 2: Data Correlation Coefficient

The data from the table shows the correlation between the distance of the fire stations and the fires. The correlation coefficient confirms that there is a direct relationship between the distance of fire stations and damages sustained. The further a fire station is from a fire, the greater the damages are as illustrated by the strong relationship of miles at 1, and damages at 0.96. The same is said for the opposite, being that the closer the fire station is to the fire, the less the damages are.

Scatterplot Data

Figure 1: Correlation Coefficient Scatterplot

Figure 1 illustrates the high correlation coefficient between the distance of a fire station from a fire. As you can see from the points on the scatterplot, there is a positively strong relationship between the two variables.

Conclusion

In conclusion, the statistical data confirms the hypothesis that there is indeed a strong relationship for the distance between a fire station and the amount of damages sustained due to fire. The further away a fire station location is from the fire, the greater the damages are. To reduce fire damage in residential areas where fire stations are located more than a mile away from populated residential areas, it would be beneficial to build additional fire stations.

Grade Point Averages and Law School Admissions Tests

Introduction

It is well known that to get into college, one must have a grade point average score (GPA) over a certain number, with the most common average being 2.5. Upon completing an undergraduate degree, many students choose to continue their education in a graduate program such as Law School. A hypothesis was formed to answer the question of whether or not student’s GPA scores would be a good indicator of how well they would perform on the Law School Admissions Test (LSAT). To answer this question a study of 82 undergraduate students entering into the class of 2000 was conducted to see if there is a correlation between student’s GPA Scores and LSAT Scores. Data from the study was used to create the following tables depicting the mean, standard deviation, and the minimum and maximum variables used to test and validate the hypothesis.

Descriptive Statistics

Table 3: Descriptive Statistics for LSAT and GPA Scores

The data for students entering Law School in Table 3 shows the mean for GPA scores to be 3.13, while the mean for LSAT scores is 597.59. The method for calculating GPA scores is not the same as it is for LSAT scores, but the perspective of either is the same, being the higher the score the better the students’ performance. The standard deviation for GPA is 0.19, and the for the LSAT it is 38.49. The minimum score for GPA is 2.57, with a maximum of 3.5. The minimum Score for the LSAT is 477, with a maximum of 704. To illustrate the similarity in the two scores we can use the percentage difference in the scores ranges. The percentage difference between the minimum and maximum GPA score is 73%, and for the difference in the LSAT scores it is 68%.

Correlation Coefficient

Table 4: Data Correlation Coefficient

The data in Table 4 illustrates the relationship between GPA and LSAT scores. The correlation coefficient between GPA and LSAT scores comes in at 0.76, which shows a moderately high level of correlation between the scores. The correlation shows that students with higher GPA Scores also score higher on the LSAT, indicating the hypothesis is correct.

Scatterplot Data

Figure 2: Correlation Coefficient Scatterplot

The data shown in Figure 2 shows the relationship between GPA and LSAT Scores. The scatterplot shows the strong correlation of students who have high GPA scores and their ability to do well on the LSAT.

Conclusion

In conclusion, the results of the statistical data show a strong relationship in a student with a high GPA score and their ability to score high on the LSAT. A high GPA score is a strong indicator of a student’s ability to do well when furthering their education by taking the LSAT to enter into Law School.

Distance and Damages

Damage

3.4 1.8 4.5999999999999996 2.2999999999999998 3.1 5.5 0.7 3 2.6 4.3 2.1 1.1000000000000001 6.1 4.7 3.8 26.2 17.8 31.3 23.1 27.5 36 14.1 22.3 19.600000000000001 31.3 24 17.3 43.2 36.4 26.1

Distance from Fire Station

(Miles)

Damages

(Thousands of Dollard)

Law School Admissions

LSAT 3.23 2.83 3.24 3.12 3.09 3.39 3.1 3.4 2.97 2.91 3.11 3.24 3.3 3.22 3.43 2.91 3.23 3.47 3.15 3.33 2.99 3.19 3.03 3.01 3.39 3.41 3.04 3.29 3.16 3.17 3.13 3.36 2.57 3.02 3.03 2.88 3.37 3.2 3.23 2.98 3.11 2.92 2.85 3.38 2.76 3.27 3.36 3.19 3.17 3 3.11 3.07 2.96 3.05 2.93 3.28 3.01 3.21 3.32 3.24 3.03 3.33 3.08 3.13 3.01 3.3 3.15 2.82 3.2 3.44 3.01 2.92 3.45 3.15 3.5 3.16 3.19 3.15 2.81 3.16 3.02 2.74 622 542 579 653 606 576 620 615 553 607 558 596 635 581 661 547 599 646 622 611 546 614 628 575 662 627 608 632 587 581 605 704 477 591 578 572 615 606 603 535 598 575 573 644 545 645 651 562 609 555 586 580 594 594 560 641 512 631 597 621 617 637 572 610 562 635 614 546 598 666 570 570 605 565 686 608 595 590 558 611 564 575

GPA

LSAT Scores