Analysis Of Chi Square Test Of Independence
We are asked to determine if gender influences the choice of a major. Conducting a Chi Square Test of Independence allows us to draw a conclusion. Two variables that are categorical is required to complete a Chi Square Test of Independence (Mirabella, 2011). The purpose of this test is to determine if variables are independent or dependent from one another. To see the relationship between two variables, we are to use cross tabulation. Cross tabulation is when we display information for two variables across from one another (Mirabella, 2011). We will learn if there is a dependent relationship between two variables.
Our null hypothesis is that one’s choice of major is independent of one’s gender while our alternate hypothesis is that one’s …show more content…
Today, the healthcare field is growing rapidly, and most of the workers are women. This is a market advantage. Pharmacists, doctors and occupational therapists are the best-paying jobs for women (Goudreau, 2012). It is business that is the most popular major. In terms of employability, business ranks high. A business equips students to work in many fields. Sales, consulting, finances, marketing, and management are examples (Goudreau, 2012).
When performing a hypothesis test to determine if the difference in sample proportions occurs by chance or randomly, the chi-square test is used. The Chi Square Test of Independence measures how well the observed distribution of data fits with the distribution that is expected if the variables are independent ("Pearson's Chi-square Test for Independence," 2008).
When constructing your categories, it is best to be careful. Based on how you divide up the data, a The Chi Square Test of Independence can provide information. However, it cannot tell you whether categories are meaningful ("Pearson's Chi-square Test for Independence," 2008). Designed to analyze categorical data, The Chi Square Test of Independence uses data has been counted and divided into categories. The test works best with data that is not continuous or parametric. Height and inches would be an example. Arranging variables into categories such as female, male, pass, and fail works perfectly ("Pearson's Chi-square Test for Independence,"
Our null hypothesis is that one’s choice of major is independent of one’s gender while our alternate hypothesis is that one’s …show more content…
Today, the healthcare field is growing rapidly, and most of the workers are women. This is a market advantage. Pharmacists, doctors and occupational therapists are the best-paying jobs for women (Goudreau, 2012). It is business that is the most popular major. In terms of employability, business ranks high. A business equips students to work in many fields. Sales, consulting, finances, marketing, and management are examples (Goudreau, 2012).
When performing a hypothesis test to determine if the difference in sample proportions occurs by chance or randomly, the chi-square test is used. The Chi Square Test of Independence measures how well the observed distribution of data fits with the distribution that is expected if the variables are independent ("Pearson's Chi-square Test for Independence," 2008).
When constructing your categories, it is best to be careful. Based on how you divide up the data, a The Chi Square Test of Independence can provide information. However, it cannot tell you whether categories are meaningful ("Pearson's Chi-square Test for Independence," 2008). Designed to analyze categorical data, The Chi Square Test of Independence uses data has been counted and divided into categories. The test works best with data that is not continuous or parametric. Height and inches would be an example. Arranging variables into categories such as female, male, pass, and fail works perfectly ("Pearson's Chi-square Test for Independence,"