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With Histograms Neeeeed Help

I need some help with my java histogram program?

Ask the user to input how many values (from 50 to 200) to be used. Write a verification of input loop to ensure their input is between 50 and 200. Generate random integers in the range of 1 - 100. As you create the random numbers, accumulate total counts for each of the number ranges on the histogram ie: 1-10, 11-20, 21-30, etc. - these values MUST be stored in an Array! Use a switch statement to put values into an array OR to print the table.

I need a bit of help for this so far this is what i have:

import java.util.Random;
import java.util.Scanner;

public class Histogram {

public static void main(String[] args) {

Scanner scan = new Scanner(System.in);

int num;

System.out.println("Please enter a number: ");

num = scan.nextInt();

while (num < 50 || num > 200)
{
System.out.println("Invalid number please reenter: ");
num = scan.nextInt();
}

int[] nums = new int[10];

}
}

beyond this i'm just completely, any help would be appreciated

Which statement about a histogram is true? HELP?

I really need help on this Answer!! I don't get it

Question:Which statement about a histogram is true?

A:Histograms can plot both positive and negative values on both axes.

B:Histograms can be used to exhibit the shape of distributions.

C:Histograms are plots of individual data values.

D:Histograms show the division of quartile regions for a distribution.

In statistics I need help in finding midpoints on a histogram and the percentage.?

1. ANSWER: Yes; valid probablity distribution because sum of percent of nurses = 1.00

3. ANSWER: 0.359


Why??
P(x > 60) = 0.25 + 0.091 + 0.018 = 0.359


5. ANSWER: STD DEV = SQRT(VARIANCE) = 13.66

Why????

x (INTERVAL MID-POINT)
24.5
34.5
44.5
54.5
64.5
74.5
84.5

P(x)
0.057
0.097
0.195
0.292
0.250
0.091
0.018

x * P(x)
1.40
3.35
8.68
15.91
16.13
6.78
1.52


x * P(x)
1.40
3.35
8.68
15.91
16.13
6.78
1.52



x^2*P(x)
34.21
115.45
386.15
867.31
1040.06
505.07
128.52
SUM = 3076.79

MEAN^2 = 2890.14
VARIANCE = SUM - MEAN^2 = 186.65
STD DEV = SQRT(VARIANCE) = 13.66

Histograms? Please help with Statistics homework! ?

I have several problems like this to do and don't understand it very well. I have read the literature over and over and still don't understand how to manually draw a histogram. The example I have makes no sense either. Help would greatly be appreciated.


(a) Find the Class Width
(b) Make a frequency table showing limits, class boundries, midpoints, frequencies, and relative frequencies.
(c) Draw a histogram
(d) Draw a relative frequency-histogram

The following data represents glucose blood levels (mg/100 ml) after a 12-hour fast for a random sample of 70 women

45 66 83 71 76 64 59 59
76 82 80 81 85 77 82 90
87 72 79 69 83 71 87 69
81 76 96 83 67 94 101 94
89 94 73 99 93 85 83 80
78 80 85 83 84 74 81 70
65 89 70 80 84 77 65 46
80 70 75 45 101 71 109 73
73 80 72 81 63 74

Use six classes

Acceleration Histogram?

You would need to know what the initial velocity is or, at least, the velocity at some point in time. Otherwise you can not determine a specific velocity. Does the object start from rest? I don't know, it doesn't say.

The velocity change during any given time interval will simply be the area under that interval of the graph.

So from 4 to 5 seconds the acceleration changes from 0 to -2. The object is slowing down. Since the area is triangular we can write:
change in velocity = (1/2)(5 - 4)(-2 - 0)
change in velocity = -1

From 5 to 6 it is constant at -2 so:
change in velocity = (6 - 5)(-2 - 0) = -2 ..... area is rectangular

And so. Just add up all the changes and the result will be the final velocity if the object started from rest. If it started with some velocity you will have to add that in.

Why would someone want to use a histogram?

Histogram has a very wide meaning and why you would want to use one depends on the application area. Histogram is not just the plot though that can be what people assume. Histogram can be summarized roughly as an inventory of what "kinds of items" you have and "how many of each kind" you have. I want to note - to clarify a point in respect to other answers - that sometimes the "types of items" are categorical, and kernel estimates have no meaning there. Then histogram is your only choice. Document indexing using term frequencies is a good example. This is the basic idea behind most of information retrieval (e.g. web search). You represent text documents with a histogram of words, that is, a list of words and their frequencies. There are usually a lot of operations that follow, but the histogram is an essential and irreplaceable step and an important part of the basic approach that is called "bag of words".Other than that, more often histogram is used as an easy (though not the best) estimate of how a variable is distributed (e.g. pixel values in an image, income levels in a population, grades of students, etc). Why you would want to know the distribution of a variable is another question. It is a kind of a statistic and has its value. You usually have a numeric variable (i.e. "interval variable") in the case of applications where you use histogram as an estimate of the density/PDF. Kernel density estimates, which sort of works like smoothing the histogram, is a better choice if you can do that. Otherwise you may have to play with the bin sizes to get an accurate feel and not be misled by a poorly tuned histogram.Another application: In computer vision, histogram appears a lot and many times helps to introduce some sort of robustness to your method. For example a bunch of techniques called local features/descriptors make use of the histogram of the image gradient in an image region. This summary representation helps you compare different images without being affected too much by variations in pixel values, shifts and tilts, etc. that change the individual pixel values significantly. So, histogram has the benefit of a summary data structure that is robust to certain changes that you want to ignore in the raw data.

What is the need of histogram processing in image enhancement?

To answer the question lets understand what is image enhancement:Image enhancement is the process of making images more useful The reasons for doing this include:– Highlighting interesting detail in images– Removing noise from images– Making images more visually appealingThere are two broad categories of image enhancement techniques – Spatial domain techniques• Direct manipulation of image pixels – Frequency domain techniques• Manipulation of Fourier transform or wavelet transform of an imageHistogram processing is a technique that operates in the spatial domain. The histogram of an image shows us the distribution of grey levels in the image Massively useful in image processing, especially in segmentationSpreading out the frequencies in an image (or equalizing the image) is a simple way to improve dark or washed out images. So to keep image enhancements histogram processing is used.I hope this helps.Cheers!!

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