- Published: November 15, 2021
- Updated: November 15, 2021
- University / College: University of Leeds
- Language: English
- Downloads: 42
Abstract
This project seeks to analyze the correlation between the number of students per state with the grade level. A simple linear regression equation and attributed graph will be applied to indicate this status.
Introduction
With the increased population of students and attributed practices to each student in various states in the US, the work of assessing and grading these students in the class performance, statistical instruments are necessary to achieve efficiency of certain measures of dispersion. Attaining efficient measures of dispersion is a guarantee of the overall efficiency of the data. In this case, a correlation between the total population of a state and the grade level of learners will be examined (Kameo, 32). A linear graph will be used to investigate this relationship
Description of data
The data for this project was retrieved from http://www. cde. ca. gov/ds/ . , and it covers 18 states and learning grades from K to grade 12
Report Total
0; 1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; Year
Alameda
; 01; 18655; 17591; 17755; 17553; 17223; 17248; 16626; 16448; 16685; 18; 16499; 16608; 1658
9; 16990; 193; 222681; 167; 2013-14
Alpine ; 02; 12; 15; 10; 11; 11; 10; 5; 5; 4; 0; 0; 1; 4; 2; 0; 90; 0; 2013-14
Amador
; 03; 294; 278; 311; 325; 299; 330; 334; 290; 328; 0; 338; 324; 336; 378; 0; 4165; 0; 2013-14
Butte
; 04; 2548; 2360; 2406; 2276; 2316; 2387; 2234; 2381; 2287; 0; 2385; 2460; 2400; 2588; 41; 310
69; 0; 2013-14
Calaveras
; 05; 452; 359; 400; 405; 372; 394; 421; 448; 473; 27; 522; 527; 519; 500; 18; 5837; 0; 2013-14
Colusa
; 06; 411; 383; 381; 333; 355; 318; 338; 326; 335; 0; 353; 367; 315; 303; 0; 4518; 0; 2013-14
Contra Costa
; 07; 13719; 12851; 13412; 12997; 13333; 13292; 13274; 13149; 13219; 0; 13516; 13104; 13281
; 13572; 301; 173020; 81; 2013-14
Del Norte
; 08; 337; 320; 364; 321; 288; 291; 291; 290; 335; 0; 285; 304; 333; 385; 0; 4144; 0; 2013-14
El Dorado
; 09; 2120; 1933; 1952; 1953; 2024; 1977; 2050; 2087; 2068; 1; 2279; 2269; 2223; 2301; 0; 2723
7; 39; 2013-14
Fresno
; 10; 17704; 15771; 15954; 15438; 15406; 14957; 14680; 14666; 14522; 1; 14863; 14886; 14281
; 15103; 228; 198460; 4; 2013-14
Glenn
; 11; 483; 360; 474; 448; 366; 413; 404; 435; 434; 0; 431; 430; 430; 421; 15; 5544; 0; 2013-14
Humboldt
; 12; 1666; 1396; 1477; 1432; 1346; 1345; 1253; 1395; 1224; 66; 1427; 1374; 1296; 1296; 61; 18
054; 0; 2013-14
Imperial
; 13; 2940; 2741; 2807; 2934; 2708; 2793; 2751; 2855; 2829; 0; 3195; 2934; 2893; 2543; 53; 369
76; 0; 2013-14
Inyo
; 14; 213; 203; 231; 212; 214; 202; 181; 186; 198; 0; 684; 720; 783; 1053; 0; 5080; 0; 2013-14
Kern
; 15; 16291; 13779; 14681; 14101; 13705; 13430; 13469; 13355; 13321; 24; 14139; 13037; 1287
0; 13412; 66; 179680; 0; 2013-14
Kings
; 16; 2643; 2220; 2313; 2273; 2142; 2129; 2097; 2076; 2103; 14; 2189; 2156; 2097; 2171; 5; 286
28; 0; 2013-14
Lake
; 17; 800; 668; 700; 724; 644; 703; 654; 662; 706; 0; 685; 702; 750; 618; 0; 9016; 0; 2013-14
Lassen
; 18; 372; 318; 340; 322; 340; 305; 325; 334; 319; 0; 369; 400; 398; 399; 0; 4541; 0; 2013-14
Los Angeles
; 19; 123935; 115731; 118322; 115599; 114908; 114826; 113619; 115656; 118308; 190; 129959
; 126350; 121305; 123249; 747; 1552704; 814; 2013-14
Madera
; 20; 2710; 2388; 2581; 2350; 2426; 2301; 2346; 2324; 2255; 0; 2284; 2276; 2289; 2331; 0; 3086
1; 0; 2013-14
Marin
; 21; 2947; 2707; 2692; 2646; 2730; 2685; 2512; 2427; 2364; 0; 2333; 2305; 2185; 2218; 42; 327
93; 0; 2013-14
Mariposa
; 22; 164; 130; 153; 133; 128; 143; 144; 146; 127; 0; 145; 156; 145; 175; 6; 1895; 0; 2013-14
Mendocino
; 23; 1099; 979; 983; 1057; 943; 941; 993; 982; 982; 0; 1025; 1071; 1006; 1080; 7; 13148; 0; 201
3-14
Merced
; 24; 4781; 4372; 4560; 4259; 4189; 4360; 4236; 4371; 4266; 0; 4234; 4194; 4232; 4304; 103; 56
461; 2; 2013-14
Modoc
; 25; 137; 101; 115; 103; 117; 114; 110; 106; 104; 0; 119; 109; 101; 118; 0; 1454; 2; 2013-14
Mono
; 26; 141; 135; 154; 134; 136; 134; 114; 152; 111; 0; 102; 117; 136; 440; 0; 2006; 0; 2013-14
Consider further description of the data
Report: state Enrollment
Gender: female and male
Type: Normal
Description
Consider the graphical description of this data in a histogram below. The graphs are deduced from the excel
The scatter Diagram
Descriptive Statistical Method
Since our data is one-dimensional, we use a simple linear regression equation t relate the two items; the students and the grades (Water Management in Reservoirs, 21). The mode of the equation is indicated as follows
Y = a +bx
Where a and b are constants, which depends on the changes of Y and X
In this case, the Y –axis is represented by the student population and the X- axis, is represented by the grade level. In the regression, we assume that, he is normally distributed with the mean 0 and variance α2. In the data analysis, we need to check the validity of this assumption. In addition, we need to check the level of correlation between the number of students and the grade level enrolled (Gerald, 4). In estimating the values of the a and b, the least square method will be used. After considering the results of the regression analysis, we settle at the final regression equation as follows
Y= 1. 0210 + 6. 564 X. This is the equation is relevant to the data discussed in this study since the correlation between the two variables is on the positive trend (David, 32).
Work Cited
Calderone, Gerald E. Statistics About Society: The Use of Federal Data in Decision-Making and Anlysis. , 1974. Print.
Kanaan, Omar. Regression-based Prioritization and Data Modeling for Customized Civil Engineering Data Collection. , 2012. Print.
Matusita, Kameo. Recent Developments in Statistical Inference and Data Anlysis: Proceedings of the International Conference in Statistics in Tokyo, 28.-30. 11. 1979. Amsterdam [u. a: North-Holland, 1980. Print.
Ruppert, David. Statistics and Data Analysis for Financial Engineering. New York: Springer, 2011. Print.
Water Management in Reservoirs. Amsterdam: Elsevier, 1989. Internet resource.
