Buying a home is probably the biggest investment you make in your lifetime. For most people, the house represents their life savings turned into bricks and mortar. But no matter the quality of construction, this house is not safe from fire, theft or other disasters. Recovering from a loss results in significant costs that most people cannot afford, even if it is a partial loss, for example when someone lose some property because of a burglary, with home insurance, you are protected and you do not have to pay a large amount at once, at a time that is often difficult on the emotionally. The purpose of this paper is to analyze the given data set based on the housing insurance claims by performing hypothesis tests and it also discusses why or why not uniform pricing scheme is appropriate.
A good insurance policy varies as much as the particular characteristics of each dwelling. As well as how to insure a house that belongs to you will vary from apartment you are renting, as well as that you just happen to acquire. For example, you'll no doubt want to ensure the structure of your home, as are goods that are inside of it. However, as a tenant, your privilege rather an insurance that will cover your belongings and furniture only, certainly, it is capital to choose an insurance plan that will cover the portion of "liability" to protect you from possible prosecution in the event of damage to a third party.
Liability insurance is a common feature which is found in each type of insurance. In general, all insurance policies cover the minimum liability, property and the repair of the house insured. We recommend that you still validate with the insurer contacted.
Discussion
The data set given for the purpose of this paper shows certain conditions that have been given in the table below, it can be seen that for every condition there is minimum and maximum value. In order to analyze the data set we have descriptive statistics, descriptive statistics are commonly encountered, relatively simple, and for the most part easily understood. Most of the statistics encountered in daily life, in newspapers and magazines, in television, radio, and Internet news reports, and so forth, are descriptive in nature rather than inferential. Compared with the logic of inferential statistics, most descriptive statistics are somewhat intuitive. Typically the first five or six chapters of an introductory statistics text consist of descriptive statistics (means, medians, variances, standard deviations, correlation coefficients, etc.), followed in the later chapters by the more complex rationale and methods for statistical inference (probability theory, sampling theory, t and z tests, analysis of variance, etc). The data collected shows that the minimum date for term started is 1/1/2010, however the maximum date 12/31/2011.
Conditions
min
max
Term start
1/1/2010
12/31/2011
State
NSW
QLD
NSW/QLD
Age
10
110
Building Type
HOUSE
UNIT
HOUSE/UNIT
Wall Type
BRICK
OTHER
BRICK/OTHER
Sum Insured
0
600000
Occupancy
LANDLORD
OWNEROCC
LANDLORD/OWNEROCC
Descriptive statistical methods are also foundational in the sense that inferential methods are conceptually dependent on them and use them as their building blocks. One must, for example, understand the concept of variance ...