Interval estimation of the population mean can be computed from functions of the following R packages:

From the data, we obtain the following information: (i) the sample size is more than 30, and (ii) the population standard deviation is known. Therefore, the appropriate test is z-test. And the function to use is

- stats - contains the
`t.test`

; - TeachingDemos - contains the
`z.test`

; and, - BSDA - contains the
`zsum.test`

and`tsum.test`

.

`t.test`

of the stats package is a student's t test, and is use when raw dataset is given. The same case for `z.test`

, but this function is specifically for z-test of known population standard deviation. When dataset is not given and only the summary statistics (mean, and standard deviation) are presented, then the appropriate functions are `zsum.test`

or `tsum.test`

. Note that, `t.test`

and `tsum.test`

are functions of the same statistical test, and that of `z.test`

and `zsum.test`

. Consider the example below,**Example 1**. The 2012-2013 SASE scores of the 33 random students from College of Science and Mathematics (CSM) of MSU-IIT were recorded: 84, 93, 101, 86, 82, 86, 88, 94, 89, 94, 93, 83, 95, 86, 94, 87, 91, 96, 89, 79, 99, 98, 81, 80, 88, 100, 90, 100, 81, 98, 87, 95, and 94. The population of these scores are believe to be normally distributed with 6.8 standard deviation. Determine and interpret the 95% and 99% confidence interval of the population mean.From the data, we obtain the following information: (i) the sample size is more than 30, and (ii) the population standard deviation is known. Therefore, the appropriate test is z-test. And the function to use is

`z.test`

, that is**Interpretation**: The true mean of all SASE scores in the school year 2013-2014 from CSM is likely between 88.01327 and 92.65340 (95% CI). And the true mean of all SASE scores for the said college and school year is likely between 87.28425 and 93.38241 (99% CI).