Tag Archives: Data Analysis

Academic Project

ACADEMIC PROJECT

What is an Academic Project?

Academic ProjectAn academic project is a formal document whose major sections include an abstract, introduction, literature review, methodology, results, discussion, and conclusions and recommendations. The process of writing and presenting an academic project is guided by certain rules. These rules may vary depending on the level of education, institution, or the supervisor. OpenBook offers high standard academic project writing services strictly following the rules provided in order to represent the students’ contribution to the body of knowledge.

Formulating a Project Title of a Project

A comprehensive project title should be brief and must identify the population of interest, and the independent and dependent variables. Students should also adhere to the stipulated requirements related to the length of the project title.

Preparing an Abstract

An abstract should provide a summary of the academic project. Generally, an abstract is placed before the table of contents. A comprehensive abstract should highlight all the essential aspects of the project. Students should be cautious not to exceed the required length of the abstract that is estimated at 150-250 words. A comprehensive summary should highlight the project’s hypothesis, objectives, methodology, and findings.

Guidelines for Writing the Introduction

In the introduction section, the student should highlight the problem area and discuss its significance. A comprehensive introduction should contain the research questions, objectives, and hypotheses that will guide the academic project. Students should distinguish an introduction from a literature review. Whereas the introduction utilizes existing literature to highlight a problem area, the section does not synthesize the referenced studies.

Conducting a Literature Review

Conducting a Literature ReviewLiterature review forms the second chapter of dissertations and theses. A comprehensive literature review highlights students’ ability to identify relevant scholarly works and synthesize their findings. Literature reviews should utilize current articles to inform future readers of the existing knowledge and establish a context for conducting their intended academic projects. The contents of a literature review should correlate to the formulated hypothesis and research questions. For example, an academic study may be intended to improve on the existing knowledge related to the implementation of bed alarms as a fall prevention intervention. Consequently, the accompanying literature review should synthesize the current knowledge related to the utilization of bed alarms in hospital settings. A student should highlight the existing knowledge gaps in the available literature that justify the proposed academic project. For instance, previous studies may have investigated the influence of bed alarms in preventing falls among geriatric patients. A student may identify a need to narrow the focus of their research to geriatric patients who have been diagnosed with chronic mental illnesses. A comprehensive literature synthesis should highlight the existing knowledge gap related to the limited studies that focused on a specific population.

Guidelines for Writing the Method/Approach Section

The methodology section should contain a discussion of the design and project implementation plan. The method section should be detailed and comprehensive to promote replicability. A project’s methodology comprises the intended population, setting, instrumentation, data collection, data analysis, and ethical considerations. A subsection may be introduced to discuss the formulated project procedure. The procedure should highlight all the executed steps and treatments performed on the independent variables to study the changes in the dependent variables. The methodology section should also highlight the proposed data analysis techniques. Students should identify the software used and data analysis tests conducted to guarantee the replicability of their academic projects.

Guidelines for Writing the Findings and Discussion Sections

The length of the findings section often varies between qualitative and quantitative projects. The findings of a qualitative study may be lengthy because of the need to discuss the identified themes and their correlation to the formulated research questions. In the case of quantitative research, the findings ought to be tabulated because they fundamentally comprise statistics. The findings section should be followed by a discussion of the implications of the concluded academic project. The discussion section explains the observed outcomes. A comprehensive discussion should highlight the identified limitations and provide a basis for conducting future studies.

Factors to Consider When Writing an Academic Project

Factors to Consider when Writing an Academic ProjectStudents may sometimes have several ideas on their academic project but no specific research question. Our writers, therefore, come in handy to help you identify a topic that will address specific research questions. They do so by thoroughly examining previous Scholarly sources to identify areas that need further research. After identifying a topic, the next important stage is to refine your topic to bring out what issue you are investigating. Our writers offer expert help to enable you bring out your argument and clearly outline the problem or gap you want to address.

Conducting literature review is an important step in project writing. You need to be able to demonstrate why your research is important and how it will expand on knowledge in that particular field. Our company helps you conduct a literature review, which is a review of material that has already been published in relevant peer-reviewed journal articles and books. Our writers through years of experience are keen on using references that you or your supervisor recommended and that are most recent and relevant to your project. There are ethical considerations for all academic projects regardless of methodology. When offering help in writing academic projects, our writers help you strengthen your project by addressing ethics that govern project writing. Our writers understand that academic projects that do not observe ethics may be rejected.

Why Seek our Project Writing Services?

Our writers are time conscious. We deliver your work within the given time-frame. Once you order your Project Writing Services, you can follow up the writing progress with OpenBook Project Team and communicate any changes you may like. OpenBook Project Team ensures deadlines are met. In addition, our writers are experts and will, therefore, ensure quality and integrity of your research by meeting the standard project writing requirements. Our writers avoid use of casual language in project writing as it may portray lack of expertise.

To ensure thoroughness, an editor is assigned to supervise your work after you make your project writing services order. The editor ensures your work is done thoroughly with every instruction taken into account. OpenBook Project Team is also responsible for ensuring you are satisfied with our services by following up to see if you may need any revisions on your work. OpenBook does not charge extra cost for work revision. In case you would like to make an inquiry on help in writing academic projects, feel free to contact us on whatsapp number: 2348028999115 or click

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SPSS DATA ANALYSIS SERVICES

SPSS DATA ANALYSIS SERVICES

Are you a bachelor’s, master’s, or Ph.D. student in need of expert to help in Data analysis for your dissertation or project? We have competent SPSS data analysts who will help you conduct simple statistics such as descriptive statistics using mean, median, standard deviation, etc. The statisticians also have years of experience in conducting advanced statistics such as inferential statistics (ANOVA, ANCOVA, t-test, regression, factor analysis, etc.). Data analysis is a process involving illustrating, condensing, inspecting and critically evaluating collected data using logical statistical techniques. Analyzed data will finally help you in arriving at conclusions and proving a hypothesis in your dissertation or project. OpenBook, therefore, offers SPSS data analysis help to students aiming to draw inductive interpretations from data.

The Types of Data Analysis Services That We Provide

The first form of data analysis is qualitative data analysis. This type of analysis helps to analyze text and individuals’ views to understand social phenomena in a natural setting emphasizing experiences, meanings, and opinions. Quantitative analysis, on the other hand, is quantifiable and has numerical results. Thus, it is used to reveal results and conclusions using statistics. OpenBook uses SPSS for this kind of data analysis.

Make use of Expert Data Analysis Services for Guaranteed Success of your Project/Dissertation

Help with Data Analysis for Capstones

Accurate data analysis will have numerous benefits to your dissertation or project and you as the researcher. It will help you avoid human bias in the research conclusions with the help of proper statistical evidence. Our expert statisticians have the rationale to choose one method of analysis over another and come up with a meaningful and accurate interpretation for your project. After ordering for SPSS data analysis services for your dissertation or project, OpenBook is trusted to structure findings from different sources to arrive at logical and valid conclusions.

In providing data analysis services, we follow acceptable norms of discipline in data analysis regarding the nature of the variables used and the population assumptions of the data sources. OpenBook advises on data recording methods to ensure objectivity and avoid mistakes in missing data, data altering, and data mining, among other common errors in data analysis. Our statisticians are also trained to maintain a precise paper trail of how data was handled for future review.

OpenBook provides a detailed description and interpretation of results. Our statisticians are trained to attain relevance and avoid inconsistency by arranging ideas using headings and subheadings to prevent misinterpretation. They use graphs, charts, and tables to present and further explain findings. Our statisticians also understand the importance of outlining any data sources and shortcomings that might affect the results.

Why Trust our Data Analysis Help?

A team of experts reviews every data analysis service order. The expert statisticians ensure that the work satisfies all the confidentiality requirements provided by the client. They also ensure that all sources are accurately referenced using the recommended referencing method. Your data analysis order is also checked for any computation errors to ensure the figures used in tables, charts, and text are consistent. Also, our services are delivered on time. Check our recent analysis excerpt from THE MODERATING ROLE OF ISLAMIC CORPORATE GOVERNANCE BETWEEN PRESSURE, OPPORTUNITY, RATIONALIZATION, CAPABILITY AND BANKING FRAUD IN KANO STATE NIGERIA and join our live chat  on whatsapp number: +2348028999115 or click

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Welcome to OpenBook Page

 

ACADEMIC PROJECT, QUESTIONNAIRE RELIABILITY CHECKING, SPSS DATA ANALYSIS, PLAGIARISM CHECKING, BOOK BINDING, BOOKS SALES, E-BOOKS DOWNLOADING, BOOK LAYING AND INDEXING,  ISBN BARCODE IMAGE GENERATION, AND BOOK PUBLISHING

 

OpenBook Sample Size Calculators 

In order to generalize from a random sample and avoid sampling errors or biases, a random sample needs to be of adequate size. What is adequate depends on several issues which often confuse people doing surveys for the first time. This is because what is important here is not the proportion of the research population that gets sampled, but the absolute size of the sample selected relative to the complexity of the population, the aims of the researcher and the kinds of statistical manipulation that will be used in data analysis (Taherdoost, 2016). While the larger the sample the lesser the likelihood that findings will be biased does hold, diminishing returns can quickly set in when samples get over a specific size which need to be balanced against the researcher’s resources (Gill et al., 2010).

To put it bluntly, larger sample sizes reduce sampling error but at a decreasing rate. Several statistical formulas or calculators are available for determining sample size.

Gill, J. Johnson, P. & Clark, M. (2010). Research Methods for Managers. Sage Publications

Taherdoost, H. (2016). Sampling Methods in Research Methodology; How to Choose a Sampling Technique for Research. International Journal of Advance Research in Management, 5(2), 18-27

OpenBook Yamane Calculator (OY Calculator, 2022)

OpenBook Yamane Calculator (OY Calculator, 2022) is a free online sample size calculator developed to help research students or other researchers from various fields worldwide, having problem in calculation using Taro Yamane Formula manually, determine sample size accurately.

Taro Yamane (1967) Formula is written as

n = N / (1 + Ne2) simplified and adjusted, to be more accurate, from Cochran’s (1963, 1975) Sample Size Formula:

Where:

  • n = Number of Samples,
  • N = Total Population,
  • e = Error Tolerance (level) or Margin of Error, 0.05
  • p = Sample Proportion, 0.5
  • z = z-value found in Z-score Table, 1.96

The table below is Z-score Table for most use confidence level or confidence interval.

Confidence LevelConfidence IntervalArea between zero and z-scoreZ-score
90%0.1090/2%=0.45001.65
95%0.0595/2%=0.47501.96
99%0.0199/2%=0.49502.58

 

By substituting for z = 1.96 and p = 0.5 in the simplified formula above, Taro Yamane Formula can be proved as follows:

e could be 0.10, 0.05 or 0.01. They are margin of errors, that can be tolerated in determining sample size, at confidence level of 90%, 95% and 99% respectively. They are used in educational and social science research studies. The most commonly and widely used is 0.05. The sample proportion p, though varies, but by default is 0.5. If you are not familiar with confidence level, confidence interval or margin of error and sample proportion – the common terms in sample size and calculation, you can click here.

One of the advantages of using OpenBook Yamane Calculator, to accurately determine sample size, is when the total population is relatively large. Secondly, you don’t need to crack your brain of any complex formula and all its variables’ values especially if you don’t have relevant knowledge in statistics. Other advantage is that as large sample size reduces sampling error to validate research findings, there are always excess samples of 16 or 15 at total population of 300,000 and above, when compared with other Sample Size Calculators, which is enough to gather much more information or data, from the respondents, about a study. To prove this, the highest sample you would ever get using OpenBook Yamane Calculator from total population of 300,000 and above is 400 and the highest sample you would ever get using other Sample Size Calculators from also 300,000 total population and above is 384 or 385. So, there are always excess samples of 16 or 15 to get much more information about a study using OpenBook Yamane Calculator.

However, the population N is to be determined first from the study area. When the population is relatively large and the exact number is unknown, then 300,000 or more can be used because any sample size gotten cannot be greater than 400 or 385 (either Taro Yamane Formula at confidence interval of 0.05 or other Sample Size Formula at confidence level of 95%, confidence interval of 5% and sample proportion of 50%).

To calculate the Sample Size n, using OY Calculator below: enter the Total Population N, then calculate by clicking on Calculate Button. To enter different Total Population N, click Reset Button.

Using OY Calculator, you may also change the default 0.05 in the margin of error e placeholder to your desired confidence interval by selecting either 0.10 or 0.01 as alternate scenario. The 300,000 in the right field of population N placeholder is to be used when the exact number is unknown at confidence interval of 0.05. The common usage of 0.05 confidence interval for a specific sample size result is to bring balance against the researcher’s resources relative to the complexity of the population. Statistically, large samples must be equal to or greater than 30 (Murray, 2009). As sample size is used to validate research findings, it must not be too small. If too small, it will not yield valid results. At the same time, if it’s too large, may be a waste of money and time.

Murray, R. Spiegel et al (2009). Probability and Statistics. The McGraw-Hill Companies Inc.

 

Population N
N_Unk_Use300000
Margin of Error e

 

The use of OpenBook Yamane Calculator can be referenced in your thesis or dissertation as:

OpenBook Yamane Calculator, 2022. OpenBook Sample Size Calculators. OpenBook Communications and Technologies, Nigeria. https://www.openbookpage.com/

 

OpenBook Cochran Calculator (OC Calculator, 2022) and OpenBook Cochran Correction Calculator (OCC Calculator, 2024)

(From Cochran’s Sample Size Formula without Adjustment or Modification of Z-score z, 1.96 at confidence interval or margin error e, 0.05 and sample proportion p, 0.5) 

To calculate the Sample Size n, using OC/OCC Calculator below: enter the Total Population N, then calculate by clicking on Calculate Button. To enter different Total Population N, click Reset Button.

Using OC/OCC Calculator, you may also change the default 1.96 and 0.05 in their respective placeholder to your desired confidence level of either 90% or 99%  by selecting 1.65 or 2.58 and 0.10 or 0.01 respectively as alternate scenarios. The 300,000 in the right field of population N placeholder is to be used when the exact number is unknown at confidence interval of 0.05 and z-score value of 1.96. The common usage of 0.05 confidence interval and 1.96 z-score value for a specific sample size result is to bring balance against the researcher’s resources relative to the complexity of the population. Statistically, large samples must be equal to or greater than 30 (Murray, 2009). As sample size is used to validate research findings, it must not be too small. If too small, it will not yield valid results. At the same time, if it’s too large, may be a waste of money and time.

Murray, R. Spiegel et al (2009). Probability and Statistics. The McGraw-Hill Companies Inc.

 

Population N
N_Unk_Use300000
Margin of Error e
Z-Score z (C. Level)
Sample Proportion p

 

OpenBook Cochran Correction Calculator, 2024 (OCC Calculator, 2024)

Sample Size can also be calculated using Cochran Sample Size Formula with the application of FINITE POPULATION CORRECTIONs (FPCs)

Cochran (1963, 1975) developed the equation to yield a representative sample for proportion of large sample.

n0 = z² pq/e²

which is valid where n0 is the sample size, z² is the abscissa of the normal curve that cuts off an area α at the tails (1 – α equals the desired confidence level is 95%), e is the desired level of precision, p is the estimated proportion of an attribute that is present in the population, and q is 1-p. The value for z is found in statistical tables which contain the area under the normal curve.

Finite Population Correction for Proportions (If small population). If the population is small then the sample size can be reduced slightly. This is because a given sample size provides proportionately more information for a small population than for a large population. The sample size (n0) can be adjusted as

n = n0 / [1 + {(n0 – 1) / N}]

where n is the sample size and N is the population size

Cochran (1977) introduced Finite Population Corrections (FPCs) based on the sampling fraction f = n/N where n is the sample size and N is the finite population size. In practice, FPCs may be ignored if f does not exceed 5%. Larger samples relative to their populations require FPCs because ignoring large sampling fractions results in biased standard errors (Cochran, 1977). Applied researchers should identify their target populations, examine their sampling fraction, and consider using FPCs because applying FPCs yields more accurate inferences for finite populations.

 

Population Size N
N_Unk_Use300000
Margin of Error e
Z-Score z (C. Level)
Sample Proportion p

 

The use of OpenBook Cochran Calculator can be referenced in your thesis or dissertation as:

OpenBook Cochran Calculator, 2022. OpenBook Sample Size Calculators. OpenBook Communications and Technologies, Nigeria. https://www.openbookpage.com/

 

OpenBook Krejcie-Morgan Calculator (OK-M Calculator, 2024)

(From Krejcie-Morgan Sample Size Formula without Adjustment or Modification of Chi-Square x², 3.841 at confidence interval or margin of error e, 0.05 and sample proportion p, 0.5)

Krejcie and Morgan (1970) Formula was introduced  as an alternative formula in computing sample size for categorical data. The formula is written as:

n = x²Np(1-p)/e²(N-1)+x²p(1-p)

Where:

  • n = Number of Samples,
  • N = Total Population,
  • e = Error Tolerance (level) or Margin of Error, 0.05
  • p = Sample Proportion, 0.5
  • x² = Chi-Square value found in Chi-Square Table, 3.841

The table below is Chi-Square Table for most use confidence level or confidence interval.

 x²0.90x²0.95x²0.99
Degree of Freedom10% (0.10)5% (0.05)1% (0.01)
12.7063.8416.635

 

OpenBook Krejcie-Morgan Calculator can be used as an alternative tool to confirm the cases of population and sample size not listed in Krejcie and Morgan Sample Size Table (1970), a well known table for sample size determination among behavioural and social science researchers. 

To calculate the Sample Size n, using OK-M Calculator below: enter the Total Population N, then calculate by clicking on Calculate Button. To enter different Total Population N, click Reset Button.

Using OK-M Calculator, you may also change the default 3.841 and 0.05 in their respective placeholder to your desired confidence level of either 90% or 99%  by selecting  2.706 or 6.635 and 0.10 or 0.01 respectively as alternate scenarios. The 300,000 in the right field of population N placeholder is to be used when the exact number is unknown at confidence interval of 0.05 and chi-square x² value of 3.841. The common usage of 0.05 confidence interval and 3.841 chi-square x² value for a specific sample size result is to bring balance against the researcher’s resources relative to the complexity of the population. Statistically, large samples must be equal to or greater than 30 (Murray, 2009). As sample size is used to validate research findings, it must not be too small. If too small, it will not yield valid results. At the same time, if it’s too large, may be a waste of money and time.

Murray, R. Spiegel et al (2009). Probability and Statistics. The McGraw-Hill Companies Inc.

 

Population N
N_Unk_Use300000
Margin of Error e
Chi-Square x² (C. Level)
Sample Proportion p

 

The use of OpenBook Krejcie-Morgan Calculator can be referenced in your thesis or dissertation as:

OpenBook Krejcie-Morgan Calculator, 2024. OpenBook Sample Size Calculators. OpenBook Communications and Technologies, Nigeria. https://www.openbookpage.com/

 

Gotten Your Sample Size from OY/OC/OK-M Calculator, What’s Next?

Now that you have gotten your sample size, from any of the calculators above, for the number of copies of your questionnaires, to be administered to your respondents, let OpenBook have the Questionnaire Reliability Checking and SPSS Data Analysis done for you. SPSS Data Analysis using Descriptive and Inferential Statistics. 

Questionnaire Reliability Checking (Cronbach Alpha) is EXCLUSIVELY FREE! Distance is not a barrier; you can upload your already ticked FORM/QUESTIONNAIRE to whatsapp number: 2348028999115.

Service Price of SSPS Data Analysis ranges from 15,000 to 70,000 in Nigeria Naira (NGN) and  100 to 470 in US Dollar (USD).

BSc/BA Research Data Analysis: NGN15,000/USD100.

MSc/MA Research Data Analysis: NGN30,000/USD200.

PhD Research Data Analysis: NGN70,000/USD470.

You can make payment by clicking here.

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