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Comparison of Temperature and Precipitation in Three Selected Cities

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Comparison of Temperature and Precipitation in Three Selected Cities

**Introduction**

Living in a highly urbanized city in the United States is every child’s dream. Aside from getting greater opportunities to practice one’s profession, living in these cities entails higher socio-economic class. However, migrating to a new environment requires in-depth reflection and analysis of the social as well as environmental situations of these prospect places. Two of the most important environmental factors to be considered are temperature and amount of precipitation. Temperature must be considered for this dictates cost of living as it affects one’s consumption of energy such as electricity, fuel and the like. This can also affect one’s physiological conditions as well as health. In addition, precipitations such as rain are nowadays being watched as it can bring serious calamity like flood.

This paper was conceptualized to compare the climates of three selected cities in terms of temperature and amount of precipitation. The researcher’s dream cities to live in after schooling are Syracuse City and Auburn City in New York, as well as Wilkes-Barre in Pennsylvania. The researcher believed that in order to make the comparison more reliable, statistical procedures must be applied. Also, facts or data must be taken from legitimate sources to make the results valid and useful.

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**Research Questions**

** **This study was directed to compare the climates of three US cities in terms of temperature and amount of precipitation. Specifically, this sought answers to the following:

- What is the climatic condition of the three cities in terms of:
- Average low temperature in January;
- Average high temperature in July;
- Average amount of precipitation.
- Is there a significant difference among the climatic conditions of the selected cities in terms of:
- Average low temperature in January;
- Average high temperature in July;
- Average amount of precipitation.

**Hypotheses**

The following hypotheses were tested at alpha=0.05:

*Null Hypotheses:*

Ho1: There is no significant difference among the cities in terms of average low temperature.

Ho2: There is no significant difference among the cities in terms of average low temperature.

Ho3: There is no significant difference among the cities in terms of average amount of precipitation.

*Alternative Hypotheses:*

Ho1: There is significant difference among the cities in terms of average low temperature.

Ho2: There is significant difference among the cities in terms of average low temperature.

Ho3: There is significant difference among the cities in terms of average amount of precipitation.

**Data Collection Method**

Three cities were considered by the researchers based on his preference to live in if given a chance after schooling. These cities are Syracuse and Auburn in New York, as well as Wilkes-Barre in Pennsylvania. In order to take some climatic facts about the three cities, the researcher made initial scout of some possible sources of data such as the World Bank database in their website, United Nations’ database and even the United States data and statistics website. The researcher also utilized the search engines such as Google and Yahoo. Finally, through these search engines, the website of National Oceanic and Atmospheric Administration (NOAA) was found. The record of NOAA includes climatic conditions of the three cities under consideration. The NOAA online weather data is made available in the website of National Weather Service Forecast Office, Binghamton New York (http://w2.weather.gov/climate/xmacis.php?wfo=bgm).

The original data from the website contains facts on all cities in the world in any given time. The data for a specific city and date can be retrieved by choosing the city, and indicating the specific date for the climatic condition, whether in daily, monthly or yearly basis. The researcher has chosen 2015 as the year, January and July as the month, and daily record was used.

The researcher only selected record composed of the cities’ records of average precipitation, average low temperature and average high temperature. The data was downloaded and then pasted in Microsoft Excel, and finally imported in Statistical Package for Social Sciences (SPSS).

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**Tools for Analysis of Data**

In order to answer the questions presented in this study, the researcher made use of descriptive as well as inferential statistical tools.

For the first research question, the average low and high temperatures including the average precipitation, the mean and standard deviation measures were utilized. For the second research question and for testing the hypotheses of this paper, the One-way Analysis of Variance or ANOVA (F-test) was used. The Analysis of Variance is a statistical tool used to compare the means of three of more sample groups. There were three ANOVA computations in this study, comparing the means of low temperature, comparing the means of high temperature, and comparing the means of the amount of precipitations per city. For each of the three ANOVA computations, the total number of cases (*N*) is 93, that is, 31 observations (*n*) per city. For those significant F-ratios (p-values < 0.05), the Scheffe’ Multiple Comparisons test (Post Hoc Test) was computed. The Post Hoc Test is used to determine which among the pairs of samples significantly differ from each other. The outputs of the analysis were condensed in tables and eventually interpreted so as to answer the research questions presented.

**Data Analysis and Results**

** **This portion presents the results of the analysis of the data collected. It is also revealed in this section the results of the hypothesis testing done.

For the first research question which is on the climatic conditions of the three cities in terms of low temperature, high temperature, and average precipitation the researcher made use of descriptive statistics such as mean and standard deviation.

Table 1:

*Average Low Temperature (January 2015)*

City | Mean | Std Deviation |

Syracuse, NY | 7.516 | 11.16 |

Wilkes-Barre, PA | 15.58 | 9.05 |

Auburn, NY | 8.516 | 10.87 |

Table 1 shows the average low temperature (in ^{o}F) in the three cities as represented by the January 2015 record. It can be seen from the table that Wilkes-Barre has the highest temperature during the said period with a mean of 15.58 with standard deviation of 9.05. The temperatures in Syracuse and Auburn are almost the same with a mean of 8.516 and 7.516 with standard deviations of 10.87 and 11.16, respectively. In terms of the mean temperature, Syracuse City is the coldest however, in terms of standard deviation, Wilkes-Barre has the most stable temperature (SD=9.05).

Table 2:

*Average High Temperature (July 2015)*

City | Mean | Std Deviation |

Syracuse, NY | 81.16 | 5.56 |

Wilkes-Barre, PA | 84.03 | 5.45 |

Auburn, NY | 80.26 | 5.76 |

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** **Table 2 presents the average high temperature of the three selected cities as measured in July 2015. It can be observed from the table that Wilkes-Barre has the highest temperature with a mean of 84.03 and standard deviation of 5.45. Following this are Syracuse and Auburn with means of 81.16 and 80.26 with standard deviations 5.56 and 5.76, respectively. This implies that in July, Wilkes-Barre has the highest temperature, yet it has the most stable temperature (SD=5.45).

Table 3:

*Average Precipitation (January 2015)*

City | Mean | Std Deviation |

Syracuse, NY | 0.05 | 0.18 |

Wilkes-Barre, PA | 0.06 | 0.13 |

Auburn, NY | 0.06 | 0.13 |

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** **Table 3 reveals the average precipitation in the three cities as measured by the amount of precipitation (in inches) in January 2015. It can be noticed from the table that the means are almost the same with Wilkes-Barre and Auburn having equal means of 0.06 and equal standard deviations of 0.13. Syracuse, on the other hand has the least average precipitation of 0.05 with standard deviation of 0.18.

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** **For the second research question, the One-way Analysis of Variance (ANOVA) was utilized. For significant F-ratios, the Scheffe’ test for multiple comparisons was used.

Table 4:

*ANOVA Results*

Variable | Sources of Variation | Sum of Squares | df | Mean Square | F | Sig. |

Low Temperature (January 2015) | Between Groups | 1198.09 | 2 | 599.04 | 5.54 | .005 |

Within Groups | 9735.03 | 90 | 108.17 | |||

Total | 10933.12 | 92 | ||||

High Temperature (July 2015) | Between Groups | 240.80 | 2 | 120.40 | 3.85 | .025 |

Within Groups | 2813.10 | 90 | 31.26 | |||

Total | 3053.90 | 92 | ||||

Precipitation
(January 2015) |
Between Groups | 0.00 | 2 | .00 | .03 | .973 |

Within Groups | 1.91 | 90 | .02 | |||

Total | 1.91 | 92 |

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** **For the average low temperature (January 2015), the analysis (Table 4) revealed that the computed F-ratio is 5.54 with a p-value of 0.005. Since the p-value is less than 0.05, the null hypothesis (HO1) is rejected. This means that there is significant difference among the three cities in terms of low temperature in January. For the July temperature, the same result was observed. As seen in Table 4, the F-value for the High temperature (July 2015) is 3.85 with a p-value of 0.025. Since the p-value is less than 0.05, the null hypothesis (Ho2) was rejected (Panik, 2005). This implies that there is significant difference among the cities in terms of the high temperature in the month of July. Finally, as expected, the mean precipitation in the three cities were not different as reflected by an F-ratio of 0.03 with a p-value of 0.973 (p>0.05). This means that the cities are just the same in terms of the amount of precipitation if the month of January.

Table 5:

*Scheffe’ Multiple Comparisons Test Results*

Cities | Climatic Condition | p-value |

Wilkes-Barre vs Syracuse | Average Low Temp | 0.012 |

Wilkes-Barre vs Auburn | Average Low Temp | 0.032 |

Wilkes-Barre vs Auburn | Average High Temp | 0.033 |

** **Since it was found from the One-way ANOVA that there is significant difference among the cities in terms of average low temperature and average high temperature, the Scheffe’ Multiple Comparison was utilized to determine which among the pairs account for significance of difference. As presented in Table 5, Wilkes-Barre’s average low temperature significantly differ (higher) from both Syracuse City (*p*=0.012) and Auburn City (*p*=0.032). In addition, Wilkes-Barre’s high temperature also significantly differ (higher) from Auburn City (*p*=0.033).

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**Discussion**

The purpose of this study is to analyze factual data regarding the climatic conditions in Syracuse City, Auburn City, and Wilkes-Barre City in order to be guided in choosing from among these cities whenever given a chance to live in these areas.

From the analysis, it was found that on the month of January, Syracuse City is the coldest, while Wilkes-Barre City is the hottest. On the other hand, during the month of July where the temperature is highest, Auburn City is the coldest among these cities and Wilkes-Barre is still the hottest. Also, from the analysis of the data, it was found that Wilkes-Barre temperature during the month of January is significantly higher then both Syracuse and Auburn. In addition, during the month of July, Wilkes-Barre temperature significantly differs (higher) from Auburn City only.

This result implies that if somebody who prefers low temperature chooses from these cities, he may better choose any of Syracuse City or Auburn City. In contrary, if someone prefers hotter temperature, he may choose Wilkes-Barre City. Finally, in terms of precipitation, there is no significant difference among the cities under consideration.

References

Panik, M. (2005). *Advanced Statistics from Elementary Point of View.* Elsevier Academic

Press, Burlington, MA 01803, USA

NOAA. (2015). *Online Weather Data Service.* Retrieved November 5, 2015

http://w2.weather.gov/climate/xmacis.php?wfo=bgm

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