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 Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike  Histograms shows frequencies (counts) or percents of value that fall in various buckets, % of area under graph over range reps % of data values in that range
 Histogram: (1) divide data into intervals of equal width, (2) count how many values fall into each, (3) make bar chart where height is equal to count
 Spikes  high concentration of data values in the range just below the spike

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