Phase 1: You are on an international company's research and data science team, and you want to understand what is the economically status of your company. You found some challenges (make up one or find an existing real problem in the company), so you decided to analyze data to help you better understand the problem or identify a potential solution. In this second Phase, you need to create 3 hypothesis test frameworks (please one of each: two tailed, left tailed and right tailed) and use that information to do a more extensive analysis and propose a solution for the problem you found (made up) from the phase 1. Based on your problem you can decide which variable you will use to test. Step 2. For those 3 hypothesis test frameworks define: Ho null hypothesis. Ha alternative hypothesis. Define the test significance level (10%, 5%, 1%, normally 5% is used but you can select other value) Using the Analysis tool from Excelusing the right statistic test. Determine if you will accept or reject the null hypothesis and accept the alternative. Step 3: Present your results in a report (APA format). The report needs to include the following sections: Introduction: Define the problem you found (real or any you made up from Phase I). Results and Discussion: Write the hypothesis test framework: Ho null hypothesis. Ha alternative hypothesis. Significance level Type of test you will use (two tailed, left tailed and right tailed). Run the test and determine if you will accept or reject the null hypothesis and accept the alternative. How those conclusions can help you to find a better solution for the problem. Explain