waren g harding essays

waren g harding essays Warren Gamaliel Harding was an affluent speaker, he gave the business a free hand, and his return to normalcy led to a fairly decent presidency, plagued with a only few political scandals. He was born in the town of Corsica, Ohio in on November 2, 1865. His first real 30b was an editor of the local newspaper, and that is what got him interested in public affairs. He was married to Florence Kling DeWolfe, against her father's wishes who was a prestigious banker of Marion. She became a major influence in his life, and as his fortune improved under her watchful eye he became more of a prominent figure in the local community then finally attracting the attention of political authorities. He won the seat on the Ohio Senate, then served on William H. Taft's committee at the Republican national convention. He ran for lieutenant governor and was shot down, then was defeated for governor; he then ran for the senatorial nomination and finally won. He liked serving in Senate and really made no important speeches or introduced any important legislation. Having respectable qualities as a senator he was nominated to run for the presidential office by the Republicans. His campaign promises is one of the better known ones, he promised to return the country to normalcy a word he used to describe the good old days. He never really challenged the any major topics in his campaign promises mainly sticking to old Republican virtues so as not to cause any conflict. He also was on the fence for other legislation at the time such as the league issues. He mainly was a indifferent machine mouthing what the party told him to and not be creative or real with his own ideas. One main reason I believe this is because he did not really want the office, but felt more at home at the Senate but could not give up the opportunity. Some topics he used in his administration were as follows. He passed ship subsidies, a high tariff, immigration re ...

Mean, Median, and Mode - Measures of Central Tendency

Mean, Median, and Mode - Measures of Central Tendency Measures of central tendency are numbers that describe what is average or typical within a distribution of data. There are three main measures of central tendency: mean, median, and mode. While they are all measures of central tendency, each is calculated differently and measures something different from the others. The Mean The mean is the most common measure of central tendency used by researchers and people in all kinds of professions. It is the measure of central tendency that is also referred to as the average. A researcher can use the mean to describe the data distribution of  variables measured as intervals or ratios. These are variables that include numerically corresponding categories or ranges (like race, class, gender, or level of education), as well as variables measured numerically from a scale that begins with zero (like household income or the number of children within a family). A mean is very easy to calculate. One simply has to add all the data values or scores and then divide this sum by the total number of scores in the distribution of data. For example, if five families have 0, 2, 2, 3, and 5 children respectively, the mean number of children is (0 2 2 3 5)/5 12/5 2.4. This means that the five households have an average of 2.4 children. The Median The median is the value at the middle of a distribution of data when those data are organized from the lowest to the highest value. This measure of central tendency can be calculated for variables that are measured with ordinal, interval or ratio scales. Calculating the median is also rather simple.  Let’s suppose we have the following list of numbers: 5, 7, 10, 43, 2, 69, 31, 6, 22. First, we must arrange the numbers in order from lowest to highest. The result is this: 2, 5, 6, 7, 10, 22, 31, 43, 69. The median is 10 because it is the exact middle number. There are four numbers below 10 and four numbers above 10. If your data distribution has an even number of cases which means that there is no exact middle, you simply adjust the data range slightly in order to calculate the median. For example,  if we add the number 87 to the end of our list of numbers above, we have 10 total numbers in our distribution, so there is no single middle number. In this case, one takes the average of the scores for the two middle numbers. In our new list, the two middle numbers are 10 and 22. So, we take the average of those two numbers: (10 22) /2 16. Our median is now 16. The Mode The mode is the measure of central tendency that identifies the category or score that occurs the most frequently within the distribution of data.  In other words, it is the most common score or the score that appears the highest number of times in a distribution. The mode can be calculated for any type of data, including those measured as nominal variables, or by name. For example, let’s say we are looking at pets owned by 100 families and the distribution looks like this: Animal  Ã‚  Ã‚  Number of families that own it Dog:  60Cat:  35Fish: 17Hamster: 13Snake:  3 The mode here is dog since more families own a dog than any other animal. Note that the mode is always expressed as the category or score, not the frequency of that score. For instance, in the above example, the mode is dog, not 60, which is the number of times dog appears. Some distributions do not have a mode at all. This happens when  each category has the same frequency. Other distributions might have more than one mode. For example, when a distribution has two scores or categories with the same highest frequency, it is often referred to as bimodal.