Use a t-statistic, with degrees of freedom "df=n\u22121"
for inference for a population mean:
"CI: x\u00af\u00b1t^{\u2217}_{df}SE" "HT: Tdf\\frac{x\u00af\u2212\u03bc}{SE}"
"where SE=s\/\\sqrt n"
Use a t-statistic, with degrees of freedom "df=n_{diff}\u22121" for inference for the difference in two paired (dependent) means:
"CI: x_{diff}\u00b1t^\u2217_{df}\/SE"
"SE=s\/\\sqrt n" Note that "\u03bc_{diff}" is often 0, since often "H_{0}:\u03bc_{diff}=0 ."
As the sample size increases the standard error will decrease, which increases the test statistic, and hence decreases the p-value
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