The Importance Of Data On Music

I conducted a survey, asking 20 females and 20 males their favorite food group for my AP Statistics project. I surveyed on Wednesday, September 27 and on Thursday, September 28 at Marshall High School. They chose from protein, grain, vegetables, fruit, and dairy. From the data, I found that 10 males and 2 females liked protein best, 3 males and 2 females liked grains best, 1 male and 1 female liked vegetables best, 3 males and 13 females liked fruit best, and 3 males and 2 females liked dairy best. Half of the males liked protein best, while most females liked fruits best. The least amount of both males and females liked vegetables. From this data, we can see that males like protein more than females do, and females like fruit more than males

The mean, average of the population, the standard deviation, deviation in the sample, and a histogram, a graph to show the percentage of the population, was prepared. The means calculated as follows: blue 0.2072, orange 0.2271, green 0.1852, yellow 0.1165, red 0.1448, and brown 0.1192. The histogram was bell shaped with three outliers, numbers outside the given range, of 55 candies, or one bag.

many boys as with girls and twice as many whites as blacks. The researchers also found that the

The preferred hand data has 50% of its results in a range of 2.6 cm, thus indicating that the results were quite consistent as 50% of the results occurred in the range of 15-17.6 cm. Whilst the rest of the data was quite spread quite as the minimum was 8.6cm and the maximum was 21.6 cm, which is a range of 13 cm. Therefore the rest of data had been spread evenly as seen in the boxplot and

One histogram shows height compared to the number of NBA players in the data set and the other histogram shows free throw percentage compared to the number of NBA player in the data set.

Perform descriptive analysis checks for data inconsistencies and missing data. For the categorical variable of “Sex”, the answers “F” “Woman” and “Female” mean the same. Be sure to combine these together. The same for “M”, “Man” and “Male”, these answers must be combined together.

The participants were all asked a series of demographic questions; age, race, gender, living arrangement and income. When the participants were asked age the results showed that nearly all of the participants were in the 18-24 range at 95% of the sample then leaving 5% between 25-30, the study also had the exhaustive bracket of 30 or older but no participants identified in this category. Race, my results revealed that ¾ or 75% of individuals identified as White, while 15% identified as other and 10% identified as Black. I also had a category for Asian, but the study had no participants within the sample. Gender, found that 70% of participants identified with being female while, only 30% male. Participants were given income brackets to choose from which results revealed that large majority of participants were of an income range of 0- $14,999 at 80% and the other 20% were of an income of 25,000-50,000. Last demographic question on the questionnaire was living arrangement, out of the 20 participants 19 of the individuals were Single, and 1 noted that they had a partner, neither married or other were chosen. The only result that confirms a portion of my research hypothesis is that the study had an elevated amount of female participants, that was more women volunteer than men, using the idea that’s one must volunteer to participate in research.

Box and whisker plot will allow me to compare the distributions because overall range and the center are immediately observed. From this one an individual can easily see the percentile of participation for different categories (Starnes). For example, one can see by looking at the 11th grader box plot that approximately 50% of juniors of HHS are doing more than 3 extracurricular activities which can be compared with different high schools.

An equal amount of males and females were used (6 males and 6 females) to optimize accuracy in results. The sampling technique used was convenience sampling, experimenters used students at the school they were studying as participants were readily available without any attempt to make the sample representative of a population. Upon selecting participants, participants were randomly allocated to either the control or experimental group, however an equal amount of male and female participants were allocated to either group.

Just finished discussing and letting the statistic guy checking our histogram. Please see the powerpoint and the excel file for the histogram.

This is relatively a small sample which does not offer a fair view of the human population as a whole. In addition, there were more females than males in the data collected. In the sample there was 139 males and 220 females. Having a small number of males examined in the sample gives us an unreliable mean. In addition, when examining a small sample of people, the mean of the groups examined can be easily altered by outliers, which gives an untrue view of the mean.

This chart shows the differences between the two categories and items. Looking at the table and the variety of the results from later within the study it seems that .77 and .74 are resulting from average took from the original data. Some results lined up with the hypothesis like Hypothesis 1, “In support of Hypothesis 1, categorical-level analyses revealed that men evaluated the potential for having sex with their close opposite-sex friend as more beneficial than did women (male M = 1.97, SD = 2.14;female M = .74,SD = 1.48;t(73) = 3.39,~ < .001, d = .34)”. (Bleske-Rechek, 2000). Thus, proving that males have different ways of thinking where the relationship is going within the friendship.

The next graph is displayed in Figure 3 and appears to be a double bar graph with the title “Afghanistan Population Pyramid.” From this picture, the author is attempting to identify the percentage of males versus females for specific age groups in Afghanistan. By using this graph the author appears to understand how to use visuals, but is not quite perfect yet. The concept is there, but the x-axis is a percentage versus an actual number which is not appropriate for a bar graph. Although the blue does not look unappealing, it could technically be wrong for this graph. Locker and Kienzler (2014), blue can mean strong, trustworthy, authoritative, cold, depressing, or gloomy. A better color scheme for this graph would be pink for females and

There are no outliers for both of the box plots. According to the boxplot, Adobe the number seem to be symmetrical. The graph is comparatively short. While Affiliated, is screwed to the left.

In the case of the survey it is even at 50% male and 50% female, out of 186 employees there are 93 of each gender. With data it can be much easier to look at just a portion of that data on a table rather than trying to look at the whole data set. When presenting the data, using a distribution table you can include charts and graphs to better understand the data being presented.