# Excel Assignment Help

Students seeking excel assignment help can refer to the below sample report and get insight of our quality. Some important aspects of statistical analysis of data are covered here like descriptive statistics, correlation co-efficient, and scatter plots. Results were interpreted and conclusions were drawn on the objective findings from the stats homework help report.

The purpose of the present study is to analyze the factors that influence the foster care in U.S., more exactly the effect of welfare benefits on Excel assignment help children entering foster using data from 2010-2014 for all 50 states and the District of Columbia (grouped in four regions). The findings have shown that all the variables Excel homework help affects in a small proportion the foster care. Moreover, there are some pay for Excel homework discrepancies of foster care among the four regions of U.S.

Part I: Descriptive Statistics and Relationships

The motivation of the present study is that foster care is one of the areas that welfare benefits can possibly have an effect on. In this context,analyzing the factors that can influence the proportion of children entering foster care each year per 1,000 Excel assignment help children born in U.S. is necessary.

In this part we created a table of descriptive statistics. As it can be observed in the table below, all the nine variables have 255 valid cases, Excel homework help meaning that there are not missing observations from the sample.

Table 1: Descriptive Statistics The average number of children entering foster care each year per 1,000 children born (Foster) is 74.73, with a minimum value of 25.29 and a Excel assignment  solution maximum value of 188.41. The standard deviation is 29.37.

In the considering data sample, the mean value of average earned income tax credit payment in 2014 (the variable EITC) is 2308.30, with a minimum value of 1841.78and a maximum value of 2875. The standard deviation is 210.73.

The average number of children receiving temporary assistance for needy families per 1000 children (TANF) is 38.19, with a statistics using Excel assignment help minimum value of 3.70and a maximum value of 166.25. The standard deviation is 26.97.

The mean value of the portion of TANF funds going directly towards childcare per \$1000 (TRANSF) is 161.71, with a minimum of 0and a maximum value of 678. The standard deviation is 130.29.

The poverty rate (Poverty) in the U.S. has an average value of 14.11, with a minimum of 7.2 and a maximum of 27.6. The standard deviation is 3.45.

In the case of control variables of regions (since they are dummy variables – binary variables which takes the value 1, if the condition is accomplished and 0 otherwise), the maximum value is 1 and the minimum is 0. The standard deviation is here quite small.

It can also be observed that there are some values for Kurtosis below 0 (negative numbers), which can indicate a distribution that is Excel problems with answers relatively flat (too many cases in the extremes), but this risk is reduced because in our case we have a large sample over 200 observations.

Here, we have construct a matrix of correlation coefficients.The strength of the correlation coefficient can be interpreted as the absolute Excel assignment  solutionvalue for r, which can be: very week (0.00-0.19), weak (0.20-0.39), moderate (0.40-0.59), strong (0.60-0.79), and very strong (0.80-1.0).

Table 2:Matrix of Correlation Coefficients To analyze the associations between the Excel homework solution considered variables,we must look at the Correlation Matrix presented in the table below. Here we must interpret the Pearson Correlation for each variable.

• First, each variable perfectly correlates positively with itself (1 defines a perfect positive correlation).
• There is a negative week correlation between Foster and EITC (r =-0.2539), meaning that a change in EITC will determine a data analysis using make my Excel assignment change in the opposite direction in Foster (when EITC increases, for example, Foster decreases);
• There is a negative very week correlation between Foster and TANF (r =-0.0301).
• There is a negative very week correlation between Foster and TRANSF (r =-0.044).
• There is a positive very week correlation between Foster and Poverty (r =0.0302), meaning that a change in Poverty will determine a change in the same direction in Foster (when Poverty increases, for example, Foster increases too);
• There is a negative very week correlation between Foster and Region NEAST (r =-0.0732).
• There is a positive very week correlation between Foster and Region MWEST (r =0.1731).
• There is a negative very week correlation between Foster and Region SOUTH (r =-0.1964).
• There is a positive very week correlation between Foster and Region WEST (r =0.1079).

If Foster is considered the dependent (predictive) variable and the rest of eight variables are independent, it can be noted that these explanatory variables are not very highly correlated with each other (the correlation coefficient between thestatistics using Excel homework help independent variables is far from beingvery close to the perfect correlation of 1). It means that multi collinearity would not be a problem in the model.

Here, we have construct the scatter plots of selected variables.

Figure 1:Scatter plot between FOSTER and EITC We have found from the previous section of the paper that there is a negative week correlation between Foster and EITC, relation which is Excel homework for money also shown by the scatter plot. It can be observed that the linear trend line is negative (the red line from the graph), and the cloud of points is dispersed rather than concentrated around this line, with some outliers. The linear relationship help with Excel homework between Foster and EITC is not a strong one, but week.

Figure 2:Scatter plot between FOSTER and TANF From the correlation coefficients we have found that there is a negative very week correlation between Foster and TANF, relation which is also shown by the scatter plot. It can be observed that the linear trend line is negative (the red line from the graph slowly decreases).The cloud of points is even more dispersed around this line compared with the previous situation.Some outliers are also presented. The linear relationship between Foster and EITC is a very week one.

Figure 3:Scatter plot between FOSTER and TRANSF From the previous part of the paper we have found that there is a negative very week correlation between Foster and TRANSF, relation which is also shown by the scatter plot. It can be observed that the linear trend line is negative (the red line from the graph decreases). The cloud of points is dispersed around this line, with a concentrationhelp with Excel assignment in the left part of the graph and several outliers. The linear relationship between Foster and TRANSF is a very week one.

Figure 4:Scatter plot between FOSTER and POVERTY From the correlation coefficients we have found that there is a positive very week correlation between Foster and Poverty, relation which is alsohelp with Excel homework shown by the scatter plot. It can be observed that the linear trend line is positive (the red line from the graph slowly increases). The cloud of points is dispersed around this line. Some outliers are also presented. The linear relationship between Foster and EITC is a very week one.

Part II: Accounting for foster care by regions

In this part, we will describe the experience do my Excel assignment  of foster care by four regions(NEAST, MIDWEST, SOUTH and WEST)characteristics. In order to do this, we must analyze the summary statistics (the mean), which are shown in the table above.

It can be observed that the minimum value of Foster is in the SOUTH region and the maximum value is in MWEST. The minimum value of EITC is in the NEAST region and the maximum value is in SOUTH. The minimum value of TANF is in the MWEST region help with Excel assignmentand the maximum value is in NEAST. The TRANSF reach their minimum value in WEST and their maximum value in MWEST. The NEAST region is the less affected by Poverty and the SOUTH has the highest rate.

Part III: Conclusion and Policy recommendation to HHS

The purpose of this study was to analyze the effects of nine variables on foster care. The key findings of the study have shown that children entering foster care each year per 1,000 children born(FOSTER) are negative and very week data analysis using Excel assignment help influenced by the number of children receiving temporary assistance for needy families per 1000 children (TANF) and by the portion of TANF funds going directly towards childcare per \$1000 (TRANSF). The Poverty rate (POVERTY) positively affects the FOSTER variable, but in aExcel assignment help very small proportion (the correlation between the variables is very week). Only the average earned income tax credit payment in 2014(EITC) seems to influence a more powerful (negative) influence on FOSTER (compared with the other considered variables), but the overall influence is still week.

When considering the four regions of U.S., all of them Excel project help influence in a very week proportion the FOSTER. However, NEAST and SOUTH determine pay for Excel assignment a negative correlation, and MWEST and WEST positive one.

The FOSTER is more pronounced in the MWEST, a region in which the number of children receiving temporary assistance for needy help with Excel assignmentfamilies per 1000 children (TANF) is the lowest and the portion of TANF funds going directly towards childcare per \$1000 (TRANSF) is the highest.

FOSTER has the lower value in SOUTH, even if this region is the most affected by Poverty. Since this conclusion seems somehow at odds with the economic logicthis topic can be for sure an extension for future research.It would be more likely that in the poor regions, because people have little money to support their children, the number of children entering foster care each year per 1,000 children born to be higher compared with the wealthiest regions. However, this topic can be analyzed in a further research, aExcel questions with answers possible explanation to this fact being the birth and mortality rate. However, a crucial factor to Excel assignment help this situation could also be the fact that this region (probably because it is perceived as the poorest from U.S.) received the highest amount of average earned income Excel homework help tax credit payment in 2014 (EITC), but the statistics using Excel assignment help subject needs further investigations, since the region (NEAST) with the lowest level of EITC did not have the highest level of FOSTER.

Given the overall findings, as a Excel project help policy recommendation to Department of Health and Human Services (HHS)we consider that since EITC was found to exercise the most powerful influence of the reduction statistics using Excel assignment help of FOSTER, the governmentExcel assignment help al bodies should focus on means to increase the average earned income tax credit payment.