Research Analysis Set of Hypothesis

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Research analysis on education effects on HIV occurrence

Abstract
HIV occurrence is one of the most important issues these days. Many researches in general, statisticians in special, are very concerned about this question. They are making great efforts in order to determine which factors are influencing the number of HIV occurrences.
Therefore, one of the top hospitals from US hired a team of statisticians to help them answering this question. The team made a regression analysis on 35 people, who were tested for HIV, and were also asked a few questions on a questionnaire design. After they were tested for HIV, they have been asked about the number of actual intimate partners they have, the age and gender. The steps and the statistical analyses are described below.
In this paper, we will make a statistical analysis in EXCEL and SPSS in order to see which are the independent factors who are influencing the number of HIV occurrences.
Introduction
The occurrence of HIV is a big issue nowadays. Many researchers tried to find what the factors that are influencing are. Bajos et al. (2011) made comparations between several national surveys with respect to this topic. Their analyses come up with the conclusion that, the HIV occurrences are mostly based on people's sexual behavior.
The analysis from this paper is made from a survey, where the people had to answer 3 simple questions: their age, gender and the number of partners they have had in the past 3 years. Our goal is to see how this 3 assumed independent factors are influencing the number of HIV occurrence.
After collecting the date, we will run some descriptive statistics, t and Chi-square test and ANOVA in order to see how good our model is.
1. Statistical Procedure
We will try to make statistical analyses to determine the relationship between education and HIV occurrence.
In order to do so, we will start with a survey. 35 people were tested for HIV and asked about their number of partners, age and gender. The output of the answers is in a table which is Table 1 from the Annex.
2. Research design
The variables we put in the table are: number of partners (x1), gender (x2), age (x3) and number of HIV occurrences per month (y). We are trying to answer the following questions:
• How are HIV occurrences and number of partners
• Which are the factors and what impact do they have on HIV occurrences

3. Statistical method
The first step in our analysis is to import the data into an EXCEL file and then to run a regression analysis. To find the correlation between the number of HIV occurences and the number of partners, gender and age we will look at the value of Multiple R.
From our analysis, the result is 0.75. That means the variables are 75% correlated.
Now we will perform a Hypothesis Testing analysis.
4. Hypotheses Testing
In order to check if the number of partners variable is significant, we will test wheter the coefficient is statistically significant or not. We will perform the following 4 steps:
Step 1 - Set the Hypothesis - Null and Alternative
Ho: =0 (the coefficient is not significant)
H1: (the coefficient is significant)
Step 2 - Set the level of significance
In general, for statistical analysis it is used 95% significance level, which means we have α = 0.05.
Step 3 - Calculating the p-value
This part is done by EXCEL, by looking at the value of the p_value coefficient.
Step 4 - Accept or Reject the Null Hypothesis (based on whether p_value ˂ α)
5. The Results
As we mentioned before, acceptance or rejection of the Null Hypothesis is done by the value of the p_value. From the Annex we get that p_value is very small (Sig. = 0.000) compared to α=0.05. So we will Reject the Null Hypothesis and Accept the Alternative Hypothesis.
Therefore, we conclude that there is enough evidence to say that the number of partners is statistically significant.
The P_values we have computed for the other two independent variables in the model,gender and age, are 0.80 and 0.6 respectively. Since they are both greater than the ...