I will do accurate statistical data analysis
I will do accurate statistical data analysis
To carry out an accurate statistical data analysis, you should build a hypothesis and scheme out your study design. Then, you should collect necessary details by preparing a sample using random and non-random selection methods1.
Get do accurate statistical data analysis
Once you have collected your data, you should clean it or ‘scrub’ it to ensure that you’re working with high-quality data2. After that, you should summarize your data and test hypotheses or use estimation for your statistical analysis1. Finally, you should interpret results in your statistical analysis1.
There are many statistical analysis methods that can be used depending on the type of data you have and what you want to achieve. Some of the most common statistical analysis methods include mean, standard deviation, regression, hypothesis testing, and sample size determination123.
Hypothesis testing in statistics is a way of testing an assumption about a population parameter or distribution using data from a sample1. It involves comparing two mutually exclusive statements, called the null hypothesis and the alternative hypothesis, to see which one is more supported by the data1. Hypothesis testing can be used to draw conclusions or cast doubt on established facts based on the nature and reason of the analysis1.
The alternative hypothesis is a statement that contradicts the null hypothesis and is what the researcher wants to prove. It is usually denoted by H1 or Ha.
The null hypothesis is a statement that assumes there is no relationship between two variables or that there is no difference between two groups. It is usually denoted by H0.
There are many statistical analysis methods, some of which include regression analysis, ANOVA (analysis of variance), t-tests, chi-square tests, and factor analysis.
Regression analysis is a statistical method used to examine the relationship between two or more variables. It involves fitting a line or curve to the data points that best represents the relationship between the variables. Regression analysis can be used to make predictions about future values of one variable based on the values of other variables.
Silver : $35
Analysis on small amount of data: quick data analysis
Gold : $75
Analysis on medium size data: deep data analysis
Platinum : $200
Advanced statistical analysis on large amount of data: rigorous data analysis
