Suppose you collect data regarding the number of text messages (dependent variable) sent in the last hour from a sample of students. Also, suppose you know that on average, people send about 2 (u=2) text messages per hour. You want to know if your sample of students sends significantly more text messages than people on average. Below are the SPSS results One-Sample Statistics Std, Error N Mean Std. Deviation Mean NumberOfTextMsgsSent! 39 2.90 1.744 279 nLastHour One-Sample Test Test Value = 2 95% Confidence Interval of the Mean Difference df Sig. (2-tailed) Difference Lower Upper NumberOfTextMsgsSenll 3.213 38 003 897 .33 1.46 nLastHour One-Sample Effect Sizes Point 95% Confidence Interval Standardizer Estimate Lower Upper NumberOfTextMsgsSentl Cohen's d 1.744 515 .177 846 nLastHour Hedges' correction 1.779 504 174 .829 a. The denominator used in estimating the effect sizes Cohen's d uses the sample standard deviation. Hedges' correction uses the sample standard deviation, plus a correction factor. Fill out the following information: In order to examine whether for your students differed from dependent variable the population, a was conducted. It was found that the sample type of statistical test sent text messages (M = SD = ) than the population, significantly more, significantly mean st. dev. fewer, a similar number of with a mean difference of t( )= P= mean difference df t-value p (sig) value 95% CIL, d= lower CI upper CI Cohen's d