INDEX NUMBER ANALYSIS ON THE PRICE OF PETROLEUM ON THE PRICE OF FOOD ITEMS

CHAPTER ONE

INTRODUCTION

Background of the study

The effect of prices of petroleum products on food items and the economy of Nigeria cannot be over emphasized. Petroleum products range from aviation fuel to kerosene just to mention a few, this is solely due to the lack of diversification of the economy. 85% of Nigeria gross domestic product (GDP) is being accounted for by the petroleum sector (Mahmud 2009). Before the discovery of crude oil in the early 70’s, agriculture was the main driver of the economy which has helped in the country’s development in these periods, there was hardly any incident to hike of products and services. The price stability of food items is of utmost importance to every nation that wants to witness growth; this is because it is only a healthy workforce that can give out their best in terms of work and productivity. Overtime there may have been some arguments about the relationship between petroleum prices and price index of food items. Some school of thought opined that prices of petroleum prices has nothing to do with prices of food items, questioning the agricultural stakeholders and traders for massive exploitation during price instability of petroleum products while the other school of thoughts are of the opinion that petroleum products does affect the prices of food items. Petroleum is believed to have an enormous bad wagon effect on the economy and even agricultural products this normally occurs in the economies of the West Africa sub-region which isn’t often diversified. For any oil producing nation that doesn’t want to know poverty of its masses then they must have to diversify their economy so as to prevent crises in one sector of the economy spilling over to the other sectors.

Food items are an essential commodity for a healthy nation, the supply of food to any nation must be done without any form of compromise as anything less than an adequate planning will lead to shortage in food supply which could affect the economy of the nation. Every meaningful government should always ensure that adequate food supply remains untouched as such shouldn’t be affected by either petroleum

Statement of problem

The fluctuation of agricultural food items in Nigeria has been a concern for some time now which is not good for a growing economy like ours. A nation that plays with its agricultural sector is a nation that would encounter shortage of food supply which may not pan out for a populous country like Nigeria. The problem of hike of food items each time there is a little change in the prices of petroleum items has led us to this study.

Significance of the study

This study would be useful to policy makers, researchers on the economy of the nation and above all the Nigerian government in tackling food scarcity in Nigeria thereby ensuring food security in Nigeria.

Aims and objectives of the study

This study seeks to study the price fluctuation of both petroleum products and food items with a view to knowing if petroleum price changes affects or influences a corresponding change in prices of food items in Nigeria.

• This study also seeks to examine the nature of relationship that exists between petroleum prices and prices of food items in Nigeria.
• This study is also intended to predicting the effect of petroleum and food item prices on the economy of the nation.
• To proffer solutions of ensuring food security in Nigeria.
  • Research Questions
• Is there a relationship between the prices of petroleum prices and the prices of food items?
• What nature of relationship exists between petroleum and food items prices?
• What are the ways one can ensure food security in Nigeria.
• Do the prices of petroleum prices and prices of food items affect the economy?

Research hypothesis

H₀: there is no significant relationship between the prices of petroleum products and the prices of food items.

H₁: there is a significant relationship between the prices of petroleum products and the prices of food items.

Scope of the study

This study is on the analysis on the prices of petroleum on the price of the food items from 1999-2013.

Limitations of the study

 

Financial constraint– Insufficient fund tends to impede the efficiency of the researcher in sourcing for the relevant materials, literature or information and in the process of data collection.

Time constraint– The researcher will simultaneously engage in this study with other academic work. This consequently will cut down on the time devoted for the research work.

• Definition of terms

 

• Petroleum: Crude oil, commonly known as petroleum, is a liquid found within the Earth comprised of hydrocarbons, organic compounds and small amounts of metal. While hydrocarbons are usually the primary component of crude oil, their composition can vary from 50%-97% depending on the type of crude oil and how it is extracted.

 

Economy: economy encompasses all activity related to production, consumption and trade of goods and services in an area. The economy applies to everyone from individuals to entities such as corporations and governments. The economy of a particular region or country is governed by its culture, laws, history, and geography, among other factors, and it evolves due to necessity.

Comparison between Lee Carter Model and CBD Model in forecasting higher age mortality

Abstract

Demographers and actuaries are very much conscious of the trend of mortality in their own country or in the world in general. This is because mortality is the basis for longevity risk evaluation. Mortality is showing a declining trend and it is expected to further decline in the future. This will lead to continuous increase in life expectancy. Several stochastic models have been developed throughout the years to capture mortality and its variability. This includes Lee Carter (LC) model which has been extended by various researchers. This paper will be focusing on comparing LC model and another mortality model proposed by Cairns, Blake and Dowd (CBD). The LC uses the log of central rate of mortality and CBD uses logit of the mortality odds as dependent variable. Analysis of comparison is done using a few techniques including Akaike information criteria (AIC) and Bayesian information criterion (BIC). From the overall results, there is no model better than the other in every aspect tested. We illustrate this via visual inspection and in sample and outof sample analysis usingMalaysianmortality data from 1980 to 2017.

Comparative analysis of annual numbers of patients admitted and discharged patients from hospital

Abstract

The main thrust of this study is to investigate the Dynamical model for the spread of rumors. In today’s anxiety-laden security environment, rumors can provide unique insights into the current grievances and fears of a given population; they can also act as powerful agents of influence. For example, by propagating rumors about civilian abuses at the hands of the government or military, an adversary can foster a sense of uncertainty and sow distrust between a government and its population. Conversely, by evaluating and understanding rumors currently circulating through a population, a government or military force can overcome obstacles to its programs, and can provide targeted messages of reassurance to the populace when necessary. Nowadays, with the emergence of the internet, rumors can be spread by instant messengers, emails, or publishing. With this new pattern of spreading, an ISRW dynamical model considering the medium as a subclass is established. Beside the dynamical analysis of the model, we mainly explore the mechanism of spreading of individuals-to-individuals and medium-to-individual. By numerical simulation, we find that if we want to control the rumor spreading, it will not only need to control the rate of change of the spreader subclass, but also need to control the change of the information about rumor in medium which has larger influence. Moreover, to control the effusion of rumor is more important than deleting existing information about rumor. On the one hand, government should enhance the management of internet. On the other hand, relevant legal institutions for punishing the rumor creator and spreader on internet who can be tracked should be established. Using this way, involved authorities can propose efficient measures to control the rumor spreading to keep the stabilization of society and development of economy.

ATTENTION; THIS PROJECT IS N35,000. THE N4500 YOU MAY SEE ON THIS PAGE IS A GENERAL PRICE FOR ALL PROJECT MATERIALS. PRICE CAN BE FIXED ON INDIVIDUAL TOPIC DEPENDING ON ITS NATURE.

INTRODUCTION

Sexually Transmitted Diseases (STDs) refers to a set of clinical infections in which a mode of transmission is through sexual contact, and in which at least, one partner is infected. Many of these infections spread predominantly through sexual intercourse, but in some others, sexual contact may play a less predominant or uncertain role. Most STDs are not, however spread through casual contact, vectors or formites.

Sexually transmitted diseases (STDs) are recognized as a major public health problem in most of the industrialized world. The World Health Organization (WHO) estimates that, in the mid-1990s, 30 million curable sexually transmitted infections (syphilis, gonorrhea, Chlamydia and trichomoniasis) occurred every year in North America and Western Europe with an additional 18 million cases in Eastern Europe and Central Asia. These counts do not include incurable Sexually transmitted diseases (STDs) such as genital herpes and Human Papilloma Virus (HPV) infections, for which no up-to-date estimates have been derived by the WHO. Approximately 74, 000 new HIV infections are estimated to have occurred in 1997 in North America and Western Europe. Centre for disease Control and prevention (Sexually transmitted diseases Surveillance – 2011).

Although some increases in incidence are documented, it is unclear, how much of this upward trend is due to improvements in case ascertainment and surveillance or to actual increase in STD incidence. Most developed countries have seen dramatic declines in the incidence of Syphilis and gonorrhea since World War II. Some eastern European countries nevertheless have recently experienced increase in these two STDs.

STDs deserves attention, not only because of the high prevalence, but also because they frequently go undetected and untreated and can result in serious reproductive morbidity and mortality. Compared with the extensive efforts devoted to research and intervention on HIV and AIDS, very little attention has been paid to other STDs. Hence there is a need to increase awareness of, at least, one central aspect of most common curable STDs – their incidence. Recent findings shows that some STDs acts as a cofactor or facilitator for HIV transmission, arguing that research on STDs other than HIV and AIDS can also contribute to better insights into HIV infections. Sexually transmitted diseases are responsible for a variety of health problems and can have especially serious consequences for adolescents and young adults. CDC-STD Surveillance (2011).

Transmission

The mode of transmission varies among the different sexually transmitted diseases. Some bacteria or virus are found in vaginal secretions or semen (e.g. gonorrhea), while others are shed from the skin of and around the genitals (e.g. HSV and HPV). Infections typically occur during sexual intercourse or when the genitals come into close contact. Infections may also occur during oral sex. It may also be transmitted during non-censenting sex acts such as rape or molestation.

The transmission of STDs is more efficient from men to women than from women to men. For example, with just one unprotected sexual encounter with an infected partner, a woman is twice as likely to acquire gonorrhea or Chlamydia. In addition, different STDs have different rates of transmission. For example, with one unprotected sexual intercourse, a woman has 1 percent chance of acquiring HIV, 30 percent chance of acquiring herpes and 50 percent chance of contracting gonorrhea if her partner is infected. Macdonald and David (2003).

Several studies on STDs have been evaluating sexual behaviors for quite a while. Following HIV pandemic from 1980-1990s, the focus on sexual behaviors evaluation intensified. The researchers have been investigating sexual behaviors in a variety of context often asking the same questions for various purposes. Some authors evaluated sexual behaviors in relation with STDs in order to assess individuals’ risk of acquiring STDs. Others concentrated on specific groups to describe and identify high and low risk population. Kennedy and ZephantaMtaturu (2006). However, statistics on STDs show no sign of abating the ever increasing number of STDs and deaths due to the fact that HIV/AIDS are common now, particularly in developing countries. As the time goes on, the trend of sexually transmitted diseases is becoming a big problem among the youth. Kennedy and ZephantaMtaturu (2006).

Prevalence estimates suggests that young people aged 15-24 years acquire half of all new STDs and that 1 in 4 sexually active adolescent females have an STD, such as Chlamydia or HPV. Compared with other adults, sexually active adolescent aged 15-19 years and young adults aged 20-24 are at higher risk of acquiring STDs for a combination of behavioral, biological and cultural reasons. For some STDs, such as Chlamydia, adolescent females may have increased susceptibility to infection because of increased cervical ectopy. The higher prevalence of STDs among adolescents also may reflect multiple barriers to accessing quality STD prevention services, including lack of health insurance or ability to pay, lack of transportation, discomfort with facilities and services designed for adults and concerns about confidentiality. CDC (2011).

According to Ayo et.al. (2013), Nigeria has a fast growing population and is confronted with numerous health challenges. With a population of more than 150 million, the country’s population is young; therefore, the future of the country rests to a greater extent, on how successful, its youth have a transition to a healthy and productive adulthood. Adebowale (2013) et al in a research work on statistical modeling of social risk factors for sexually transmitted diseases among female youths in Nigeria argues that, STDs remain a major public health challenge because of their health consequences, several complications especially among women who excessively bear long term consequences. It was also stated that the prevalence of STDs among Nigerian female youths is 17 percent, arguing that STDs causes infertility in women and increases the risk of transmission of HIV/AIDS. Adopting a multi-staged probability sampling to select respondents among women of child bearing age (15-49 years), the study used data from records of ICF Macro Calverton, in conjunction with National Population Commission, Nigeria in 2008.

In light of this, this paper investigated the effect of the incidence of sexually transmitted diseases and survival among different age groups and gender in the target population using the age and gender of the patient, duration of hospital stay and type of sexually transmitted disease as independent variable. Three diseases were considered namely: Staphylococcus, Urinary Tract Infection (UTI) and Retroviral disease (RVD).

APPLICATION OF MULTIPLE REGRESSION ANALYSIS ON MEDICAL DATA

CHAPTER ONE

INTRODUCTION

1.1 Background of the study

 

Discriminant analysis is a procedure that can be used to build Discriminant functions which are linear functions of p-variables that can be used to describe or elucidate the differences among two or more groups. The goals of discriminant analysis include identifying the relative contribution of the p variables to separation of the groups and finding the optimal plane on which the points can be projected to best illustrate the configuration of the groups. Another use of discriminant analysis is the prediction or allocation of observations to groups, in which linear functions of the variables are employed to assign an individual sampling unit to one of the groups. The measured values in the observation vector for an individual or object are evaluated by the classification function to find the particular group to which the individual most likely belongs.

 

Interest in human development before birth is widely spread because of the interest in knowing more about our beginning and the desire to improve the quality of life. The intricate process by which a baby develops from a single cell is miraculous and few events are more exciting than a mother‟s viewing of her embryo during an Ultrasound examination. Human development is a continuous process that begins when an Oocyt (ovum) from a female is fertilized by a sperm (spermatozoa) from the male. By accepting the shelter of uterus, the foetus also takes the risk of disease or malnutrition and of biochemical immunological and hormonal adjustment

Until the beginning of the Nineteenth Century, far more attention was paid to the collection and presentation of data than to their interpretation. Large volume of data were usually collected and frequently misinterpreted if indeed interpretation was attempted. However, since that time, the importance of scientific approach in the interpretation of data has been realized and great steps have been achieved in the development of appropriate methods.

In modern days, statistics has played a significant role in Biological, Pharmaceutical and Medical Sciences (Cornfield,1952). The application of multivariate statistical techniques to biological and medical data has dominated the areas of evidence-based medicine. Multivariate methods are relevant in virtually every branch of applied medicine, pharmacy and public health. They come into play either when we have a medical theory to test or when we have a relationship in mind that has some importance for medical decision or policy analysis in public health. Multivariate methods are also used in other disciplines.

Multivariate methods are prominently used on data to test a theory or to estimate a relationship in different disciplines. In some cases, especially those that involve the testing of medical theories, a formal multivariate model is constructed. The model consists of multivariate technique that describes various relationships. In most cases, the model is used to make predictions in either the testing of a medical theory or the study of a policy impact in pharmacy and public health.

Kirkwood and Stern (2008) defined discriminant analysis and classification as the multivariate techniques concerned with separating sets of objects or observations and with allocating new objects or observations to previously defined groups. As a separation procedure, it is often employed on a one-time basis in order to investigate observed differences when causal relationships are not well understood. The immediate goals of discriminant analysis and classification are to describe the differential features of objects so as to find Discriminant function whose numerical values are such that the collections are separated as much as possible and to sort new objects or observations into two or more classes or groups.

 

In clinical situations, the status of a patient is assessed by the presence or absence of a disease. There are many factors to consider which may or may not correlate with the incidence of the disease. There has been numerous retrospective medical research studies published each year that review past medical records and charts of former patients to help determine some of the risk factors (or causing agents) of diseases that are of interest. Finding the risk factors and the potential risk factors can help to prevent the development of the disease. For all of the diseases, most of the risk factors considered are categorical variables i.e. variables taking on two or more possible values. (Hosmer and Lemeshow, 1989), two prominent statisticians, stated that „the logistic regression model has become the standard method of analysis in this situation.‟

Logistic regression analysis is also called “Binary Logistic Regression Analysis”, “Multinomial Logistic Regression Analysis” and Ordinal Logistic Regression Analysis”, depending on the scale type where the dependent variable is measured and the number of categories of the dependent variable. Logistic regression is divided into two; Univariate Logistic Regression and Multivariate Logistic Regression (Stephenson, 2006).

Like any other model building technique, the goal of the logistic regression analysis is “to find the best fitting and most parsimonious, yet biologically reasonable model to describe the relationship between an outcome (dependent or response) variable and a set of independent (predictor or explanatory) variables” (Hosmer and Lemeshow 1989). This statement motivates the purpose of this study to identify risk factors for low birth weight (LBW) in newborn infants using the statistical tools of logistic regression analysis.

The use of logistic regression dates back to 1845. It first appeared during the mathematical studies for the population growth at that time. The term logistic regression analysis comes from logit transformation, which is applied to the dependent variable. This case, at the same time, causes certain differences both in estimation and interpretation (Anderson, 2008)

In many application areas, such as epidemiological and biomedical studies, where outcomes may be occurrence or nonoccurrence, mortality (dead or alive), and so forth, logistic regression is the standard approach for the analysis of binary and categorical outcome data. Logistic Regression Analysis (LRA) extends the techniques of multiple regression analysis to research situations in which the outcome variable is categorical. In practice, situation involving categorical outcomes are quite common. In the setting of evaluating an educational program, for example, predictions may be made for the dichotomous of success/failure or improved/not-improved. Similarly, in a medical setting, an outcome might be presence/absence of disease. The focus of this study is on the situations in

which the outcome variable is dichotomous, although extension of the techniques of LRA to outcomes with three or more categories (e.g improved, same, or worse) is possible.

 

In this Twenty First Century, statistics play an important role in many simulations, modeling and decision-making processes. This implies the need for statistical research in every facet of medicine; especially the evidence-based medicine. Anderson (2008) mentioned that the critical factor that separates statistical research from other ways of knowing the medical world is that statistical research is purely scientific in nature. In this sense, Science refers to both a system for producing medical knowledge and the knowledge produced. Also Science is a combination of an orientation towards a set of procedures, techniques, knowledge and instruments for gaining knowledge.

1.2    Broncho-Pneumonia

Pneumonia is an illness, usually caused by infection, in which the lungs become inflamed and congested, reducing oxygen exchange and leading to cough and breathlessness. It affects individuals of all ages but occurs most frequently in children and the elderly.. Historically, in developed countries, deaths from pneumonia have been reduced by improvements in living conditions, air quality, and nutrition. In developing world today, many deaths from pneumonia are also preventable by immunization or access to simple, effective treatments (Anthony, 2010).

Pneumonia can be caused by bacteria, viruses and fungi. Streptococcus pneumonia and Haemophilus influenza type b (Hib) are the most common causes of bacterial pneumonia while respiratory syncytial virus is the most common viral cause of pneumonia. A yeast- like fungus- Pneumocystis jiroveci is often responsible for pneumonia deaths in HIV-infected infants.

Broncho-pneumonia or bronchial-pneumonial or bronchogenic pneumonia is a type of pneumonia characterized by multiple foci of isolated, acute consolidation, affecting one or more pulmonary lobules. It is one of two types of bacterial pneumonia as classified by gross anatomic distribution of consolidation (solidification). The other being lobar pneumonia. Broncho-Pneumonia is less likely than lobar pneumonia to be associated with streptococcus.

The broncho-pneumonia pattern has been associated with hospital acquired pneumonia, and with specific organisms‟ staphylococcus aurous, klebsiella coli and pseudomonas. In bacterial pneumonia, invasion of the lung parenchyma by bacteria produces an inflammatory immune response. This response leads to a filling of the alveolar sacs with exudates. The loss of air space and its replacement with fluid is called consolidation.

Broncho-Pulmonary Dysplasia (BPD) is a chronic type of lung disease prevalent among infants. This disease if present in a pregnant mother leads to low birth weight of infants at birth. It is a serious lung condition that affects infants. It mostly affects premature who need oxygen therapy (oxygen given through nasal prongs, a mask or a breathing tube). Most infants who develop BPD are born more than ten weeks before their due dates and weigh less than 2 pounds (about 1kg) at birth, and have breathing problems (Jobe, 2001).

1.3    Low Birth Weight

Low Birth Weight (LBW) is described as a birth weight of a live born infant of less than 2.5kg regardless of gestational age. Subcategories include; Very Low Birth Weight

(VLBW) which is less than 1.5kg and Extremely Low Birth Weight (ELBW) which is less than 1.0kg. Normal Weight at term of delivery is 2.5kg – 4.2kg. Most normal babies weigh above 2.5kg by 37 weeks of gestation. Intrauterine growth restriction refers to delayed growth within the uterus, which then leads to low birth weight. Some babies are just small and happen to weigh less than 2.5kg at birth, just like some adults are smaller than others. Though this is considered low birth weight, in these cases, it is not abnormal nor a cause for concern.

Using the discriminant and logistic regression is of interest to this study. We will use a sample of not less than 400 of infants drawn from an underlying population of children with low birth weight (kg). These children were confined to a neonatal intensive care unit, they required incubation during the first 12 hours of life, and they survived for at least 28 days and their weights measured four weeks later. Healthy infants are denoted by while, Infected infants by (1). Factors that contribute to the risk of Broncho-Pulmonary Dysplasia (BPD) include high blood pressure in mothers, hypercholesterolemia in mothers and family history of tobacco smoking, among others (Eneh, 2011).

In strict terms, the application of statistical techniques to biological and medical data is called Biostatistics. Generally speaking, biostatistical methods are relevant in virtually every branch of applied medicine, pharmacy, nutrition and public health. They come into play either when we have a medical theory to test or when we have a relationship in mind that has some importance for medical decision or policy analysis in public health. Biostatistical methods in medicine are more or less empirical analysis using data to test a theory or to estimate a relationship in medicine, pharmacy, public health and other areas.

In some cases, especially those that involve the testing of medical theories, a formal statistical model is constructed. The model consists of statistical equations that describe various relationships. A biostatistical analysis begins by specifying a statistical model. Once a statistical model has been specified, various hypotheses of interest can be stated and empirically tested in terms of the unknown biological or medical parameters. An empirical analysis requires data which are used to estimate model parameters and to formally test hypotheses of interest. In most cases, the model is used to make predictions in either the testing of a medical theory or the study of a policy‟s impact in pharmacy and public health (Rencher, 2002).

Some statistical models in medical research may contain dichotomous factor; in form of a person is male or female; a person does or does not have a disease in question, to mention but a few. In all of these examples, the relevant information can be captured by defining a classification discriminant model.

1.4    Statement of the Problem

Birth weight less than 2.5kg is categorized as Low Birth Weight (LBW). It remains a significant public health problem in both developed and developing countries. These infants with LBW encounter greater neonatal morbidity and mortality and significantly higher rates of physical and mental handicaps later in life (Pope, 2010). Taking the infants population globally, the proportion of babies with a LBW is an indicator of a multifaceted public-health problem that includes the sex of an infant as well as the birth weight and weight four weeks after birth. Also, the mother‟s age and mother‟s occupation are important variables that could predict the LBW of the infant considered in the study. Therefore, the main problem which comes up in this particular study is how to construct linear discriminant and logistic regression models that are capable of predicting the Broncho-Pneumonia(BPn) status of the infant using mother‟s age, mother‟s occupation, baby‟s sex, baby‟s weight at birth and baby‟s weight four weeks after birth as predictor variables. The core research issue is therefore to explore the predictive powers of both the Linear Discriminant Model and Logistic Regression Model as regards statistical modeling.

However, since the models comprise discrimination and classification, it is in the interest of the researcher to classify some infants as affected and unaffected patients of Broncho Pneumonia using Linear Discriminant and Logistic Regression Models. Hence, a suitable prediction model will be developed to satisfy the best methods of validation as well as diagnostics of statistical decisions. Moreover, the Linear Discriminant Model and Logistic Regression Model could be used to predict the BPn status of new cases of infants.

 

1.5    Aim and Objectives of the Study

The aim of this study is to investigate application of multiple regression analysis on medical data. The broncho-pneumonia status in infants using linear discriminant and logistic regression models, and this will be achieved through the following objectives; by

1. constructing a linear discriminant and logistic regression models that are capable for predicting the Broncho-Pneumonia status in infants;
2. predicting the Broncho-Pneumonia status of some infants (random selected cases) using the developed models;
3. comparing the predictive powers of the two models for Broncho-Pneumoni
4. determining the predictor that has the most discriminating ability among the predictors.

1.6      Significance of the Study

The Linear Discriminant and Logistic Regression Models built in this study will give effective guide in evidence-based medicine. That is, to achieve useful projections of the BPn status of infants so as to isolate factors responsible for such. On the other hand, the study will assist medical researchers to ascertain the prevalence of BPn using the developed models.

1.7    Scope of the Study

The purpose of this study is to develop the models based on five predictors; Weight at birth, Weight four weeks after birth, Sex, Mother‟s age and Mother‟s occupation. The five independent variables are incorporated in both the linear discriminant and logistic regression models as the most relevant factors considered and captured by the study.

 

The study will also focus on North Central Zone, out of six geo-political zones of the Federation. The sample taken from two health tertiary institutions would be used for the analysis on prevalence of BPn among infants which lead to Low Birth Weight (LBW) in infants.

 

1.8   Definition of Terms

Broncho-Pneumonia (BPn): Is a type of pneumonia characterized by multiple foci of isolated, acute consolidation, affecting one or more pulmonary lobules.

Broncho-Pulmonary Dysplasia (BPD): Is a chronic type of lung disease prevalent among infants, this disease if present in a pregnant mother leads to low birth weight of infants at birth.

 

Low Birth Weight (LBW): Is described as a birth weight of a live born infant of less than 2,500g (5 pounds 8 ounces) regardless of gestational age.

 

Discriminant Function: Is a multivariate technique concerned with separating distinct sets of objects (or observations) and it gives the rule for allocating (observations) to previously defined groups.

 

Logistic regression or Logit deals with the cases where the response variable consists of two or more categorical values.

Make an Ethnographical explanation of countries infected with Corona virus in Africa and their percentage

Kenya, Ethiopia, Sudan and Guinea announced their first confirmed cases of coronavirus on Friday as the disease has now spread to at least 18 countries in Africa.

Other African countries that reported cases of the disease are Morocco, Tunisia, Egypt, Algeria, Senegal, Togo, Cameroon, Burkina Faso, the Democratic Republic of the Congo (DRC), South Africa, Nigeria, Ivory Coast, Gabon and Ghana. Most of the countries’ totals are still in single figures

PURCHASE 10