The Sumerians Were The Most Successful Ancient...

Introduction The Sumerians were the most successful ancient civilization. The first reason is they created the first written language. The second reason is they achieved many things. The last reason is that they invented many things. Cuneiform The Sumerians were the most successful ancient civilization because they created the first written language. For example, without the Sumerians, we humans would not have the invention of writing. Their writing was called cuneiform. Cuneiform is when they took a stylus and imprinted writing on clay tablets. The Sumerians would sometimes also imprint on wax, stone, and metal. Cuneiform is considered the most significant among the many cultural contributions of the Sumerians. Cuneiform writing is traced back from c. 3500 - 3000 BC. The writing wasn t first actually words. They used pictographs for writing in their records. Instead of writing letters â€Å"s-u-n†, a Sumerian would imprint a pictograph of what they had as a sun on a clay tablet. Also, they used symbols that represented traded goods and livestock. The Sumerians used writing to keep records and to keep their stories. Before the actual writing on the clay tablets was created, the Sumerians originally had tokens. The tokens were items that represented words. They were kept safe together in a sealed clay envelope. The way the Sumerians knew what was in the envelope was that they press the tokens into the clay on the outside. The reason that they had the tokens inShow MoreRelatedThe Most Influential Innovators Of The Ancient World Essay1510 Words   |  7 Pagessouth flowing into the Persian Sea. Sandy river valleys covered most of the south and mountain ranges dotted the north. This land was also known as the Fertile Crescent. Mesopotamia is one of the first major of civilization along with others that sprung up along major rivers around the world at approximately the same time. 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Murder of Roger Ackroyd Free Essays

Have you read any Agatha Christie yet? Because she is extremely awesome and not boring and conventional like you might think. In fact, her 1926 novel The Murder of Roger Ackroyd was so controversial when it came out (due to a twist ending that I’m not going to reveal) that critics were divided and other mystery writers aghast. In this mystery a widow has apparently committed suicide one year after her husband’s mysterious death. We will write a custom essay sample on Murder of Roger Ackroyd or any similar topic only for you Order Now The town doctor confirms the death and later dines with a friend (and the wealthiest man in town), who was also close with the widow. After the doctor leaves the man’s house for the evening, he is called back only to find his friend has been stabbed in the neck. And there we have the murder of Roger Ackroyd. Lucky for (almost) everyone, a strange foreigner has recently moved to the town for his retirement. He is none other than the famous Belgian detective, Hercule Poirot, and after a little coaxing from Ackroyd’s niece, he takes on the case and begins investigating the murder with the good doctor as his sidekick. There are a whole household of intriguing suspects, each of which would benefit from Ackroyd’s death and every one of them seems to be hiding something. In this book, as in the other Agatha Christie novels I’ve read, the strength lies in the balance between a great mystery (lots of clues, red herrings, and teasing hints) and a masterful sense of character and psychology. Truly a perfect mystery. This is the first Hercule Poirot book that I’ve read, and although I’ve seen some TV adaptations of Poirot stories and had a general familiarity with his character I’ve been told by a friend that I would get even more out of The Murder of Roger Ackroyd if I had a little more Poirot under my belt. Which is great because I can’t wait to read some more†¦ How to cite Murder of Roger Ackroyd, Essay examples

Gm 533 Final Paper free essay sample

Gm 533 Final Paper Executive Summary An analysis was performed for Quick Stab Collection Agency. This agency specializes on relatively small accounts and avoids risky collections such as debtor that tends to be chronically late with payments or is known to be hostile. The collection business can be very profitable. Quick Stab Collection Agency has been known to purchase small accounts for $10. 00 to collect a debt of $60. 00. The profitable of this agency depend critically on the numbers of days to collect the debt, the size of the bill and the discount rate offer. QSCA has asked us to find a relationship between the size of the bill and the days collected if any. In this data set there’s variable DAYS is the number to collect the payment, and also the BILL would be the amount of the overdue bills. The data will define that the TYPE=1 for residential accounts and the 0 for commercial accounts. A 95% confidence level was chosen. Introduction The strategy for QSCA Company it depends on how fast they can collect the debt and the amount of money received above what they paid for the account of course their intend is to get all of the amount but they realize that that may not those offering discounts in order to get payment. We will randomly select accounts from January to June that have been designated has overdue in the data set and try to establish a relationship between the size of the bill and the numbers of days to collect. In order to give management the tools need it to make decisions as to better handle accounts collections. Research Purpose The purpose of this analysis was to determine if there is a relationship between size of bills and days to collect the bill, But we have to ask the question how do we determine such a relationship if any and based to the data set given is their enough information to come to a conclusive decision. There is a sentiment with in QSCA that such a relation does exist. Hypothesis Analysis and Method Data Sample Having collected data for 6 months in both residential and commercial accounts we have a date set of 96 accounts both residential and commercial. The data set capture recorded dates the bill have been delinquent the amount of the bill and the type of bill. A copy of the survey can be found in the document sharing on the course website. Analysis Methodology In developing the criterion, a 95% confidence level was chosen and regression analysis along with a scatter plot. Computed Value of Test Statistic From the data set collected, the following test statistics were obtained: |Regression Analysis | | | | | | | | | | | | | | | |r? |0. 079 |n |32 | | | | |r |-0. 281 |k |1 | | | | |Std. Error |81. 430 |Dep. Var. |Bill | | | | | | | | | | | |ANOVA table | | | | | | | |Source |SS |df |MS |F |p-value | | |Regression | 17,097. 6041 |1 |17,097. 6041 |2. 58 |. 1188 | | |Residual | 198,925. 6146 |30 |6,630. 8538 | | | | |Total | 216,023. 2188 |31 | | | | | | | | | | | | | | | | | | | | | |Regression output | | | |confidence interval | |variables | coefficients |std. error | t (df=30) |p-value |95% lower |95% upper | |Intercept |219. 1587 |34. 7654 | 6. 304 |5. 98E-07 |148. 1582 |290. 1592 | | | |Descriptive statistics | | | | | |Days | |count |32 | |mean |53. 2 | |sample variance |604. 95 | |sample standard deviation |24. 60 | |minimum |13 | |maximum |94 | |range |81 | | | | |Descriptive statistics | | | | | |Bill | |count |32 | |mean |168. 34 | |sample variance |6,968. 49 | |sample standard deviation |83. 48 | |minimum |46 | |maximum |311 | |range |265 | | | | Scatter plot: [pic] Interpretation: Regression Analysis The r score of -0. 281 shows that our data a relatively has no strong positive correlation. The r score does not indicate that there is a positive relationship between the two variables. However the r square result was a result of 0. 079 wish would show only 7. 9% of the variance between the two data points. The standard error of 34. 7654 shows a relatively small sampling error in the data, or that there is too much error in the sample data. The F score of 2. 58 indicates that the linear relationship between the days and the bills isn’t particularly strong. The P value of 5. 98 is also too high to indicate a strong linear relationship. Descriptive Statistics We took a descriptive statistics for both data we used. The mean indicates that the days were 53 seconds. The range for the data set seems rather small at 81 seconds from 13 seconds to 94 seconds. The mean for bills was 168 or 16. 8 percent. This data also has a range of 265 or 26. 7 percent to a 31. 1 percent. Scatter Plot The scatter plot shows no indication between days and the bills. As you see that the day data decreases as the bill also decreases. Which they do not appears to have any variance from the line the days of the data points generally decreases with the bill data. Recommendation Conclusion References Bowerman, Bruce L. O’ Connell, Richard T, Orris, J. B; and Murphree, Emily S. 2010. Essentials of Business Statistics. New York: McGraw- Hill, Irwin . Microsolf Excel. Microsoft Corporation. Version 5. 0. 1997 Mega Stat Copyright 2009 by J. B Orris is a statistical add- in for Microsoft Excell, handcrafted by J. B Orris of Butler University. References Berenson, Mark L. , and David M. Levine. 1999. Basic Business Statistics. New Jersey: Prentice-Hall. Long, Lori. 1986. â€Å"Surveys from Start to Finish. † Info-Line 1-14. Microsoft( Excel. Microsoft Corporation. Version 5. 0. 1997. PHStat(. Prentice-Hall. 7th Edition. 1999.