A local businessman has a smartphone kiosk at the mall. He has made new signage that he thinks may attract more customers than the current sign. He randomized 30 days to split between a treatment group and a control group. On each day designated for the treatment group, he put up the new sign; for each day designated for the control group he put up the old sign. The results of the experiment showed that the mean number of smartphones sold while the new sign was up is five more than the mean number of smartphones sold with the old sign. To test whether the results could be explained by random chance, the businessman created the table below, which summarizes the results of the 1,000 rerandomized trials of the data (with differences of means rounded to the nearest one smartphone).

According to the simulations, what is the probability that the treatment group's mean is greater than the control group's mean by five smartphones or more, and what can be concluded regarding this result? Assume a probability of less than 5% is significant.
Treatment Group Mean − Control Group MeanFrequency
−77
−618
−520
−446
−397
−2103
−1123
0152
1138
2107
392
457
523
613
74

__The probability that the treatment group's mean is five smartphones or more greater than the control group's mean is 40%, and the results suggest that the original difference in means could be the result of random chance.
__The probability that the treatment group's mean is five smartphones or more greater than the control group's mean is 23%, and the results suggest that the original difference in means could be the result of random chance.
__ The probability that the treatment group's mean is five smartphones or more greater than the control group's mean is 4%, and the results suggest that the new sign generates more sales than the old sign.
__The probability that the treatment group's mean is five smartphones or more greater than the control group's mean is 1.7%, and the results suggest that the new sign generates more sales than the old sign.