Essay on D. H. Lawrence and Baby Tortoise

Essay on D. H. Lawrence and Baby Tortoise Essay on D. H. Lawrence and Baby Tortoise Sammie Godfrey D.H. Lawrence ! D.H. Lawrence was born in Eastwood, Nottinghamshire, England, on September 11, 1885. He attended Beauvale Board School (now renamed Greasley Beauvale D. H. Lawrence Primary School in his honor). He became the first local pupil to win a County Council scholarship to Nottingham High School in Nottingham. He left in 1901, working as a junior clerk at Haywood's surgical appliances factory, but a severe case of pneumonia ended this career. Lawrence went on to become a full-time student and received a teaching certificate from University College, Nottingham, in 1908. He created sixteen poems in his lifetime including Baby Tortoise, Moonrise, and How Beastly the Bourgeois Is. With a long life of suffering from tuberculosis, Lawrence died in 1930 in France, at the age of 44. ! Lawrence wrote during 20th-century English literature. I have read Baby Tortoise, Trees in the Garden, and Whales Weep Not! Baby Tortoise addresses being born alone to fend for yourself and how hard it is to be on your own. The poem says â€Å"The first day to heave your feet little by little from the shell, Not yet awake, And remain lapsed on earth, Not quite alive. Lawrence speaks about life and how beautiful it is even from birth. Trees in the garden addresses beauty in nature. The poem says â€Å"And the ghostly, creamy coloured little tree of leaves white, ivory white among the rambling greens how evanescent, variegated elder, she hesitates on the green grass as if, in another moment, she would disappear with all her grace of foam!† He talks about how beautiful nature is and that it could

Example of Confidence Interval for Variance

Example of Confidence Interval for Variance The population variance gives an indication of how to spread out a data set is. Unfortunately, it is typically impossible to know exactly what this population parameter is. To compensate for our lack of knowledge, we use a topic from inferential statistics called confidence intervals. We will see an example of how to calculate a confidence interval for a population variance.​ Confidence Interval Formula   The formula for the (1 - ÃŽ ±) confidence interval about the population variance. Is given by the following string of inequalities: [ (n - 1)s2] / B ÏÆ'2 [ (n - 1)s2] / A. Here n is the sample size, s2 is the sample variance. The number A is the point of the chi-square distribution with n -1 degrees of freedom at which exactly ÃŽ ±/2 of the area under the curve is to the left of A. In a similar way, the number B is the point of the same chi-square distribution with exactly ÃŽ ±/2of the area under the curve to the right of B. Preliminaries We begin with a data set with 10 values. This set of data values was obtained by a simple random sample: 97, 75, 124, 106, 120, 131, 94, 97,96, 102 Some exploratory data analysis would be needed to show that there are no outliers. By constructing a stem and leaf plot we see that this data is likely from a distribution that is approximately normally distributed. This means that we can proceed with finding a 95% confidence interval for the population variance. Sample Variance We need to estimate the population variance with the sample variance, denoted by s2. So we begin by calculating this statistic. Essentially we are averaging the sum of the squared deviations from the mean. However, rather than dividing this sum by n we divide it by n - 1. We find that the sample mean is 104.2. Using this, we have the sum of squared deviations from the mean given by: (97 – 104.2)2 (75 – 104.3)2 . . . (96 – 104.2)2 (102 – 104.2)2 2495.6 We divide this sum by 10 – 1 9 to obtain a sample variance of 277. Chi-Square Distribution We now turn to our chi-square distribution. Since we have 10 data values, we have 9 degrees of freedom. Since we want the middle 95% of our distribution, we need 2.5% in each of the two tails. We consult a chi-square table or software and see that the table values of 2.7004 and 19.023 enclose 95% of the distribution’s area. These numbers are A and B, respectively. We now have everything that we need, and we are ready to assemble our confidence interval. The formula for the left endpoint is [ (n - 1)s2] / B. This means that our left endpoint is: (9 x 277)/19.023 133 The right endpoint is found by replacing B with A: (9 x 277)/2.7004 923 And so we are 95% confident that the population variance lies between 133 and 923. Population Standard Deviation Of course, since the standard deviation is the square root of the variance, this method could be used to construct a confidence interval for the population standard deviation. All that we would need to do is to take square roots of the endpoints. The result would be a 95% confidence interval for the standard deviation.