Sorry, no.
The order of decimal numbers, from low to high, to the nearest thousandths, is as follows: 0, 0.001, 0.002, 0.003, ... , 0.,484, 0.485, 0.486, .... , 0.509, 0.510, 0.511, ... etc.
To know for sure, when you want to compare two positive numbers, divide the number that you think is higher by the other number. The answer has to be greater than 1. If not, then your assumption is wrong.
Let us assume 0.51 is greater than 0.485. Take the ratio:
0.51/0.485 = 1.05, which is greater than 1. Hence, the assumption is correct.
Since lengths are involved in this problem, we need not consider negative numbers. However, in case you have to compare one positive number with a negative number, remember that all positive numbers are always greater than negative numbers.
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1 > 0.051 < 55 = 051 < 05
1,000 is M. 051=51 and 51 is L (for 50) I (for 1). There is no Roman numeral for 0, so 1,051 in Roman Numerals is MLI.
Ignoring the decimal points, multiply them as if they were whole numbers (ignoring any leading zeros)Put the decimal point into the answer by counting how many digits in total were after the decimal points in the multiplication and put the same number after the decimal point in the answer (inserting leading zeros if necessary).0.009 bx 0.051 → 9 x 51 = 459 (ignoring the leading zeros)There are 3 + 3 = 6 digits after the decimal points (009 and 051), so 6 digits after the decimal point in the answer: 0.000459 (inserting 3 leading zeros)
The p value (also sometimes called alpha or probability level) is the percentage chance that the results of a statistical test are due to random error. So a p value of .01, for example, would mean that there is a 1% chance that the results are an error.p is also the cut-off where a test is considered statistically significant. In social sciences, significance is assumed (and therefore the hypothesis supported) when p < .05. Other fields have different cut-offs, and there are times when a researcher may argue for a higher or lower p value.It is important to note that p is only relevant to statistical significance. It has no bearing on the size or practical importance of results. As a common criticism of statistics is that a p value of .049 is "significant" while .051 is not, most researchers rely as much if not more on measures of effect size and practical application than on statistical significance. However, p remains the accepted convention for hypothesis testing.
001-010: i, ii, iii, iv, v, vi, vii, viii, ix, x 011-020: xi, xii, xiii, xiv, xv, xvi, xvii, xviii, xix, xx 021-030: xxi, xxii, xxiii, xxiv, xxv, xxvi, xxvii, xxviii, xxix, xxx 031-040: xxxi, xxxii, xxxiii, xxxiv, xxxv, xxxvi, xxxvii, xxxviii, xxxix, xl 041-050: xli, xlii, xliii, xliv, xlv, xlvi, xlvii, xlviii, xlix, l 051-060: li, lii, liii, liv, lv, lvi, lvii, lviii, lix, lx 061-070: lxi, lxii, lxiii, lxiv, lxv, lxvi, lxvii, lxviii, lxix, lxx 071-080: lxxi, lxxii, lxxiii, lxxiv, lxxv, lxxvi, lxxvii, lxxviii, lxxix, lxxx 081-090: lxxxi, lxxxii, lxxxiii, lxxxiv, lxxxv, lxxxvi, lxxxvii, lxxxviii, lxxxix, xc 091-100: xcli, xcii, xciii, xciv, xcv, xcvi, xcvii, xcviii, xcix, c