The question asks about the area covered by a bell-shaped curve from \(-6\) sigma to \(+6\) sigma in a normal distribution. This can be understood using the properties of the normal distribution and the empirical rule (also known as the 68-95-99.7 rule).
A normal distribution is a symmetric, bell-shaped curve that is characterized by its mean (\(\mu\)) and standard deviation (\(\sigma\)). In a standard normal distribution:
The area covered by the curve between \(-6\) sigma to \(+6\) sigma will include virtually all of the data, since this range captures the data so far from the mean that the tail ends of the distribution are considered.
For \(-6\) sigma to \(+6\), the area under the curve is approximately \(99.999666\%\). This value can be determined by understanding cumulative distribution function values or through statistical tables and software.
Thus, the area covered by a bell-shaped curve from \(-6\) sigma to \(+6\) sigma is 99.999666\%, which aligns with statistical analyses of normal distribution tails.
This comprehensively explains why the correct answer is 99.999666\%, ruling out other options which denotes different (smaller) areas.

| PRODUCTION UNITS | ||||||
| Month | A | B | C | D | E | F |
| April | 310 | 180 | 169 | 137 | 140 | 120 |
| May | 318 | 179 | 177 | 162 | 140 | 122 |
| June | 320 | 160 | 188 | 173 | 135 | 130 |
| July | 326 | 167 | 187 | 180 | 146 | 130 |
| August | 327 | 150 | 185 | 178 | 145 | 128 |
