#statistical analysis help

Different Types of Statistical Analysis

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In practice, Data collection and Data Analysis involves two approaches: Qualitative and Quantitative approaches. Each approach has diverse kinds of objectives and statistical methodology.

Quantitative research Methodology is useful in testing the assumptions and theories which are already Qualitative research is useful in understanding the concepts and formulating the theories. Experimental research and surveys are examples of quantitative research.

Quantitative Research

It focuses on testing the hypothesis we claim about the problem.

Expressed by numbers, tables, and graphs

Needs many observations

The questionnaire should be in closed form i.e. with multiple-choice questions

Qualitative Research

It focuses on developing and formulating a hypothesis

Expressed by words or text

Needs a few observations

The questionnaire may be in an open form i.e. respondents can write a few sentences about the question asked.

Data Collection methods:

Quantitative Research: Quantitative data collection involves four different types

. They are:Experimental data: In this case, the variables are known and are being controlled to understand the causes and effects. Survey Data: Here, the data collection is in the form of questionnaire but it should be in closed form as mentioned earlier and the survey can be done through any mode such as direct, telephonic, or online forms.Direct Observation: Here, the data is collected by observing the respondent either by letting them know about that or not. In addition, the variables for the study cannot be controlled in this type of data collection. Content Data analysis: It records the number of times a certain word is present in the textual data and analyze the pattern of them. For the Quantitative method, I will collect or survey 400 samples of students from the university and ask them to answer for the satisfaction they got with their professors teaching on a scale from 1–5. Then, with the collected data, statistical data analysis

Harry is a pizza shop owner, and he’s perplexed to prefer a better location among two locations that he already shortlisted. He created up his mind to conduct a study to opt for the quintessential area. Location A is narrow, and he notices that there’s a high school two blocks away, some business offices accessible, and a Laundromat not far away. Location B is more extensive and next to a market with some business offices scattered around the space, amidst many vacant tons. If you were Harry, which might you choose?

Mark Twain once quoted, “FACTS ARE STUBBORN THINGS, BUT STATISTICS ARE PLIABLE.”

You are a statistician in many ways. Statistics is that the technique of conducting a study of a couple of specific topics by aggregation, organizing, decoding, and eventually presenting data. Statistics are used to analyze what’s happening within the world around us. In this data-driven world, all activities of ours are monitored by someone else every time. Statistics hold a key position in nearly every field like Research, Innovation, Commerce, Trading, etc.; therefore, the application of statistics is incredibly comprehensive.

Statistics help us to convert whatever occurs in the past can be used in predicting the future. Let us take some examples which will help you realize the role of statistics in your daily life.

1. Forecasting Weather

Do you ever watch the weather outlook throughout the day time?

We all tend to watch weather forecasts. Have you ever thought of how does one get that data and how we use that information?

Forecasters use computer models applied and build on statistical ideas. These models compare previous weather with the present climate and predict future climate.

2. Emergency Management Agency

What if the forecast reports that a cyclone is close at hand or the tornadoes are possible to occur? Emergency management agencies get in the gear mechanism to be able to rescue folks. Emergency groups believe in getting informed by statistics once danger may occur.

Statistics employed mainly by the scientist. They use their skills to gather relevant knowledge. Otherwise, it ends up in a loss of cash, Time series data.

3. Predicting Disease

Statistics play an enormous role in the field of medicals. Before prescribing any medication, the scientist should show a statistically valid rate of effectiveness. For instance, studies have shown that smoking causes 80–90 % of cancer. The Data analysis ought to tell you that just about all cancer areas associated with smoking which if you would like to possess a reasonable probability of avoiding respiratory organ cancer, you should quit smoking.

4. Genetic Engineering

Many people are grieved with diseases as a genetic disorder, and these diseases will probably be passed on to their kids. Statistics analysis is essential in regulating the probabilities of a replacement baby being laid low with the illness. Genetic Engineering offers the chance of cures for disease and infinite material enhancements to lifestyle.

5. Political Campaigns

Statistics is vastly vital in politics. Candidates consult citizen polls to see wherever and the way they campaign. News media ask their models once they try and predict who the winner is.

6. Insurance

What is insurance? All of us are insured, whether it’s medical, life or any other insurance. Statistics are employed to work out what risk insured poses to an insurance company, what share of policies is probably going to pay, and the way abundant cash a corporation will expect to pay in claims.

7. Quality Assurance

Companies create thousands of products daily, and every company should confirm that a decent quality item is oversubscribed. However, a company cannot take a look at every item that they ship. Thus, they use statistics to check a couple of, known as a sample, of what they create. If the sample passes quality tests, then the corporate assumes that everything created among the cluster referred to as a batch, are excellent.

Shortly, there are numerous ways to mess up and make false conclusions.

The clustering technique in Statistical Analysis is used to determine the subsets as clusters in the data using the specified distance measure. However, this technique cannot be applied easily for longitudinal or time-series data. In this blog, I will discuss some of the methods used for modeling longitudinal or panel data using the Clustering Analysis technique as explained in Schmatter (2011).

Longitudinal data is actually a sample of observations which are measured repeatedly over time. And, nowadays, longitudinal/repeated measure data or panel data exists in all areas of Applied statistics such as finance, psychology, economics, and social sciences. Most studies deals with analyzing homogeneity in such Time series data (Diggle et al 2002), however, there are few researchers’ shows interest in analyzing the heterogeneity in such data and they proposed different modeling technique for the same.

Let us now discuss the applicability of the model-based clustering technique by means of an example as discussed in Schmatter (2011). The data consists of 237 teenagers who use marijuana for the year 1976–1980. The use of marijuana is categorized into three types as never, not more than once a month and more than once a month. This gives the idea that the data contains the categorical variables in this study. The following figure represents the sample of 10 observed responses to the use of marijuana usage among the 237 teenagers.

Data Analysis Services | Statistical Data Analysis | Statistical Consulting Firms - Statswork

Professional statistical Data Analysis Services are able to meet the requirements of any customer. We'll help Statistics Services you to collect, analyze, interpret all the data you need. Methodology can be defined as the rationale for the methods used in each study.“ Methodologies ” refer to the overall approach to the research process, from the theoretical underpinning to the collection and analysis of data. Statswork is a pioneer statistical consulting company providing full assistance to researchers and scholars. Statswork offers expert consulting assistance and enhancing researchers by our distinct statistical process and communication throughout the research process with us.

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Data Analysis Services | Statistical Data Analysis | Statistical Consulting Services – Statswork

Professional statistical Data Analysis Services are able to meet the requirements of any customer. We'll help Statistics Services you to collect, analyze, interpret all the data you need. Methodology can be defined as the rationale for the methods used in each study.“ Methodologies ” refer to the overall approach to the research process, from the theoretical underpinning to the collection and analysis of data. Statswork is a pioneer statistical consulting company providing full assistance to researchers and scholars. Statswork offers expert consulting assistance and enhancing researchers by our distinct statistical process and communication throughout the research process with us.

Contact Us:

 Website: www.statswork.com

 Email: [email protected]

 UnitedKingdom: +44-1143520021

 India: +91-4448137070

The problem with unadjusted multiple and sequential statistical testing

 In most Statistical Analyses, researchers often wish to get sufficient power to balance the cost spent for the experiment such as in medical experiment. The most common statistical technique is that using sequential sampling of data until the desired condition is satisfied. However, using this technique leads to an inflated rate of type I and type II error rate. In this blog, the Statistical Method which deals with the sequential sampling procedure are discussed. Statswork offers statistical services as per the requirements of the customers. When you Order statistical Services at Statswork, we promise you the following – Always on Time, outstanding customer support, and High-quality Subject Matter Experts

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