Final Project

For the final project, I will be analyzing the year over year change in Florida state science assessment scores for 5th graders from 2016 and 2017 for seven local counties. If we are continually improving our schools and teaching methods, we could hope that year over year we are improving our assessment scores. I used RStudio to complete my hypothesis analysis.

Null Hypothesis:

There is not a year over year improvement of state assessment scores.

Alternative Hypothesis:

There is a year over year improvement of state assessment scores.

This is the data I used:

District Name	2016	2017
HERNANDO	53%	55%
HILLSBOROUGH	52%	50%
MANATEE	46%	43%
PASCO	49%	50%
PINELLAS	55%	53%
POLK	45%	44%
SARASOTA	64%	64%

#x = scores from 2016
#y = scores from 2017


x <-c(53, 52, 46, 49, 55, 45, 64)
y <-c(55, 50, 43, 50, 53, 44, 64)
t.test(x,y)

##
##  Welch Two Sample t-test
##
## data:  x and y
## t = 0.19713, df = 11.88, p-value = 0.8471
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -7.189348  8.617920
## sample estimates:
## mean of x mean of y
##  52.00000  51.28571

Sample Means:

Scores from 2016: 52

Scores from 2017: 51.29

P-Value: 0.8471

Significance Value of .05

.8471 is greater than or equal to .05 which means there is not a significant difference between the two means.

plot(x,y, xlab = "2016", ylab = "2017")

abline(lm(y~x))

Although the two values are not significantly different, the mean for y is less than the mean for x meaning that the null hypothesis is true, there was not a year over year improvement in assessment scores.