Mathematical mean, or average, is the most important statistic used in the analysis of my data collection. The means were a representation of the average percentage in each group, and were the numbers essential for the calculations of t-probability, ANOVA and standard error.

The t-probability was an important statistic used for testing the statistical significance between two groups. By calculating the statistical significance using t-probability I found that the t-probability of the hFOB- and hFOB+ at 34°C incubation was 59%, the hFOB- and hFOB+ at 37°C incubation was 99%, and the hFOB- and hFOB+ at 34°C incubation was 95%,making the difference between groups statistically insignificant. This demonstrates that there is no significant variation between the hFOB- and hFOB+, revealing that KM110r infection has no effect on the number of living osteoblast cells.

The standard error was calculated by dividing the standard deviation for each group by the square root of the n variable in each group. In the case of standard error, a relatively small standard error is a sign of a good sampling. The standard error calculated for each group is an indicator of how much the mean could fluctuate either up or down if a different collection of the same number of samples were collected. If error bars shown on a graph do not intersect one another, they are statistically different from one another. If they intersect with other error bars, the error overlaps and so any difference that occurs is not statistically significant.

ANOVA tests whether there is statistical significance among the means of more than 2 groups, i.e. it tests the variability among group means. The ANOVA test was employed to confirm the difference among U2OS infected growth patterns at all incubation temperatures. ANOVA uses sum of squares, degrees of freedom, and mean squares to produce an F-ratio and a Sig. value. The F-ratio (a measure of how different the means are relative to the variability between each sample) is considered significant if it is greater than 1. The result of the F-ratio was 15.72, which is much greater than 1. This indicates that the means of the groups are significantly different. The sig. value lists the probability that the population mean difference is zero. The sig. value must have an alpha level of less than 5% to be significant. The sig. level determined by ANOVA in this experiment was 0.001, or 0.1%, which is much less than 5%. This sig. value confirms that the means of the groups are statistically different, since the population mean difference could be zero a mere 0.1% of the time.

The statistical analyses used in this assessment of data verify the reliability of the data.