Statistical And Descriptive Methods For Solving Business Problems Within Insurance

Leach, C. (1979). Introduction to statistics: A nonparametric approach for the social sciences. New York: Wiley.

Descriptive statistics are digits that are used to summarize and describe a given range of data (Klenke, 2008). Basic descriptive data includes, mean, median, mode, variance and standard deviation. The data can be rearranged in an ascending order as follows:

The last few weeks we covered descriptive statistic: the central tendency, variability, correlation and Z-score. Today’s session is a little bit different, we will be talking about statistical significance. Statistical significance is the level of risk one is willing to take to reject or accept a null hypothesis while it is true and it separate random error from systematic error. When doing a study or research, the statistical significance shows that the difference obtained were not caused by chance. Inferential statistics, the T-test, partition noise from bias by studying a random sample than the population in which we are interested and from the results we infer. The advantage of using sample than a population, it is convenient, saves time, energy and money because n is smaller than population and above all it helps to control systematic and random errors. When we are making a conclusion, we should have a certain confidence or probability of being right and that is called the alpha level; which the risk you are willing to

The preceding paper analyzes how descriptive statistics is used in Kaiser Permanente. In addition to that it also highlights the use of inferential statistics in the organization. Apart from that the paper evaluates the use of four levels of measurement in the organization. In addition to that the role of proper interpretation of statistical information in efficient decision making has also been described by the paper.

When we look around us, we may not recognize that statistics is all around. Before I began to take this course “Statistics for Managers” I was not aware of how statistics actually worked. The first idea that came to my mind about statistics was probability. Not knowing statistics and probability are related because they both determine a possible outcome. Throughout this course I have learned what statistics is and how it works. In this paper, I will describe descriptive and inferential statistics, hypothesis developing and testing, the selection of statistical tests, and how to evaluate statistical results in analyzing data.

At a glance scatter plots show whether a relationship exists between two sets of data. This data will determine correlations between students taking the SAT and ACT. Because this scatter plot is falling from left to right it has a negative slope, so therefore there is a negative correlation between these two sets of data. Although these points are falling, it is not a clear negative relationship since the clustered points are not in a straight line. Therefore, this relationship is a weak, negative relationship.

1. Generate a scatterplot for income ($1,000) versus credit balance ($), including the graph of the best fit line. Interpret.

In order to figure out how variables relates to each other and the connections among the variables, or one can predict the other. I will choose three quantitative variables or two quantitative variables and one categorical variable on each pairs. I will also use graphs of scatter plots; regression and correlation to understand that how one variable affect other two variables. There are six groups below:

Curve fitting involves producing a statistically derived best-fit line of data points on the graph; not a hand-drawn or estimated line connecting data points.

(TCO 3) Before performing linear regression, it is important to ensure that a linear relationship exists between the dependent and independent variables by plotting observed

3) The performance of personal and business investments is measured as a percentage, return on investment. What

For this scatterplot the coefficient of determination is no longer very close to zero. This means that the slope may be significantly different from zero which in turn would mean that there is a significant correlation between the two variables. In order to check this we consider a hypothesis test for the slope of the regression line. The null and alternate hypotheses for this test are

Statistics is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the physical and social sciences to the humanities. Statistics are also used for making informed decisions – and misused for other reasons – in all areas of business and government. Statistical methods can be used to summarize or describe a collection of data; this is called descriptive statistics. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, and then used to draw inferences about the process or population being studied; this is called inferential statistics. Both

The goal of ordinary least squares (OLS) regression is to best predict one variable?s behavior against another.

Hansen Consulting proudly presents the following statistical information for Otto’s Auto parts. Statistics is a branch of mathematics that makes it possible for you to gain an edge over your competitors by providing a method for collection of data, and a way to summarize and quantify it to represent real world observations from which predictions can be made. Statistics also includes stochastic modeling, which is a powerful tool that incorporates random variables to predict future outcomes. For decades insurance companies have successfully profited from using stochastic modeling for making predictions of unknown entities. Stochastic models can be run hundreds or even thousands of times to show the