Relationship Between Gsas And School Level Characteristics

State the independent variable (IV) and the dependent variable (DV) from the case study Level C, Case 2.

b. Dependent Variable: the variable that I am measuring (it depends on the independent variable)

The null hypothesis that there is no relationship between the amount of coffee consumption and GPA (p = .62).

Part B: How might each of the following concepts affect the results of the study?

There is a significant difference in ethnic diversity versus a typical public school system in Georgia. At KC 46.5% of the student population is African American (Kennesaw, GA public school average is 23.2%) 32% of the students are Caucasian, 5.5% Hispanic, 8.5% Asian, 5.6% are at least two races or more and less than 1% of the student population is made up of American Indian or

4b) Are there any significant correlations between the variables? If so, explain which variables are correlated, and describe the nature of the correlation (i.e., positive or negative).

Controls used in the statistical model other than just the charter status are student background, grade cohort in school effects, and school exact effects which are likely to affect student achievement. In the model, i, j, k and t represent individual schools, students, grades, and years; s is the test score for each student for all of his/her school years, α a represents an disregarded school-specific characteristic that does not get any modification over time,δ is an disregarded grade-cohort influence within each school, γ is an disregarded restriction reflecting the potential effect of charter school attendance on s; C is an gauge variable that equals one if the school is a charter school and zero otherwise, x is a 1 x K vector of K observable factors affecting s, β is a K x 1 vector of disregarded parameters, and v is a random error term (Buddin, Richard, and Ron Zimmer.

Our main research questions are: is determining a school’s success, all about testing? and if it’s not, what other ways can we gather data about a school’s performance to satisfy these policies?

Another basic research question is: There is a relationship between schools in each state with GSAs and state level characteristics.

* Activity 4.2: Identify nearby areas with schools containing similar demographic statuses as the evaluation group by December 2013

Moreover, as GSS is used to obtain data from participants, some findings conveyed that that the race and gender gap

There were one hundred and thirty two heterosexual women who returned the survey and 112 lesbian women participated but had a higher response rate. Women were surveyed from eleven different states. These states was Georgia, Ohio, New Jersey, Louisiana, Florida, Indiana, Illinois, Texas, California, Alabama and Washington. Most surveys were returned from the state of Georgia. The average age for heterosexual women was forty five and the average age for lesbian women was thirty seven. There were mostly white women who participated having eighty one percent for heterosexual and seventy nine percent for lesbian women. Heterosexual women had to be in a dual n income marriage where both spouses worked more than part time. Lesbian women had to been in a relationship for at least one year and both

Schools in high-poverty areas with most children in need of free or reduced lunch, tend to do well with these new regulations. However, schools will less kids eligible for free or reduced lunch do not do so well, and a lot of districts in this category have dropped the program. Theory is that schools with more children than not eligible for free or reduced lunch, are more likely to eat what is served to them. “Some of our students show up for breakfast and haven’t had anything to eat since lunch the day before” (Hill). The Executive Director of Nutritional services points out a harsh fact, and the good these lunch programs bring to table.

The null hypothesis would reflect as if there is no difference between both variables (Malec & Newman, 2013). The null hypothesis would indicate that there is no relationship between GPA and IQ. The alternative hypothesis would indicate another option, which is contrary to the null and may or may not be directional (Malec & Newman, 2013). The alternative hypothesis would be, that there is a relationship between GPA and IQ. This writer agrees with

Null hypothesis: Private school students do not score better on standardized tests than public school students