Statistics Essay Example | Topics and Well Written Essays - 4750 words

Statistics - Essay Example According to basic probability we divide the figure of favourable outcomes by the total number of possible outcomes in our sample space. If we're observing for the chance it will rain, this will be the number of days in our record that it rained divided by the total number of similar days in our record. If our meteorologist has data for 100 days with similar weather conditions, and on 80 of these days it rained (a favourable outcome), the probability of rain on the next similar day is 80/100 or 80%. In view of the fact that a 50% probability means that an experience is as likely to happen as not, 80%, which is greater than 50%, means that it is more likely to rain than not. But what is the probability that it won't rain Keep in mind that because the favourable outcomes represent all the possible ways that an event can occur, the sum of the different probabilities must equal 1 or 100%, so 100% - 80% = 20%, and the probability that it won't rain is 20%. The following scatter plot with a fitted line shows that there is a positive relationship b/w selected 15 student's maths and science scores. ... represent all the possible ways that an event can occur, the sum of the different probabilities must equal 1 or 100%, so 100% - 80% = 20%, and the probability that it won't rain is 20%. 2. The table below gives the marks of 15 students in tests in 2 subjects: Students 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Maths 29 45 27 19 39 46 25 38 39 43 49 21 38 46 37 Science 36 42 31 26 42 41 25 41 40 40 43 23 39 45 38 a. Scatter graph of the maths and science scores with best fitted line The following scatter plot with a fitted line shows that there is a positive relationship b/w selected 15 student's maths and science scores. Part 2b will be the evidence to prove this hypothesis that student's math scores will be positively related to their science scores. Correlation coefficient (r = + 0.936) this magnitude shows that it's highly correlated and the positive sign shows that there is a positive correlation between the variables. So we conclude that as one variable increases other one will also increases. b. Comment on the position of the line of best fit and any correlation between the scores. Although one objective of correlation is a line fitted to the data, this line is not used to predict an unknown value of one variable when given a value of the other variable; it simply shows the relationship between the two variables. This best-fit line is the one that minimizes the sum of squared deviations between the points and the line, measured vertically (along the Y axis). The Bivariate Correlations procedure computes Pearson's correlation coefficient. Correlations measure how variables or rank orders are related. Before calculating a correlation coefficient, screen your data for outliers (which can cause misleading results) and evidence of a linear relationship. Pearson's

Emerging influences in the United States healthcare system Essay

Emerging influences in the United States healthcare system - Essay Example re organizations influence trends in service delivery since every other organization combines business strategies that help in the best performance of the institution (Bowden & Smits, 2012). This paper attempts to analyse to what extent workforce tsunami, Hospital Acquired Conditions policies and Malcolm Baldrige National Quality Award system influences current trends in the United States healthcare system. It is evident that there are a lot of skills that the old workers in America have accumulated over time; but in the next ten years or so, this story may hit the economical headlines and human interest. People talk about age as just being a number, but at the same time I think this saying should only work best during birthdays because aging as far as the American workforce is generally concerned is becoming an economic threat. This factor, generally referred to as the workforce tsunami, cuts across all businesses and workplaces, including the human healthcare facilities. These facilities invest so much in the old, trusting them for their long term experience without considering the fact that a time will come when most of these old employees will pass on. This occurrence will have the risk of greatly affecting the American workplaces and facilities in the healthcare system may lack workers for an unknown period before the right experts are obtained to replace the aging and perishing g eneration. This basically will have a potential detrimental impact on the lives of Americans, especially those in their sick beds during such an unfortunate occurrence (Laing eta al., 2009). Realistically and evidenced by statistical data, it is expected that about 10,000 baby boomers will continue turning to that age of sixty five years every year until we get to 2030. A more realist observation is that about a quarter of a million of all Americans find themselves celebrating sixty five years of age on monthly basis. Looking at these figures may not indicate a great impact, but the